Tag deep-learning 一大堆深度学习论文

原文链接：http://blog.csdn.net/GarfieldEr007/article/details/51541308http://blog.csdn.net/GarfieldEr007/article/details/51541308

Tag deep-learning [159 articles] 

Recent papers classified by the tag deep-learning.

    

 

✔ Deep Learning without Poor Local Minima

  

(23 May 2016)

by Kenji Kawaguchi

posted to deep-learning learning-theory machine-learning by memming on 2016-05-24 21:56:26  along with 1 person

Abstract

 

✔ Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records

  

Scientific Reports, Vol. 6 (17 May 2016), 26094, doi:10.1038/srep26094

by Riccardo Miotto, Li Li, Brian A. Kidd, Joel T. Dudley

posted to deep-learning by hans_meine on 2016-05-23 10:04:13 

 

✔ Deep learning

  

Nature, Vol. 521, No. 7553. (28 May 2015), pp. 436-444, doi:10.1038/nature14539

by Yann LeCun, Yoshua Bengio, Geoffrey Hinton

posted to deep-learning neural-networks by vankov  on 2016-05-22 21:20:13  along with 27 people

 

✔ Where Do Features Come From?

  

Cogn Sci, Vol. 38, No. 6. (1 August 2014), pp. 1078-1101, doi:10.1111/cogs.12049

by Geoffrey Hinton

posted to deep-learning neural-networks by vankov  on 2016-05-22 21:12:41  along with 1 group

Abstract

 

✔ Modeling language and cognition with deep unsupervised learning: a tutorial overview.

  

Frontiers in psychology, Vol. 4 (2013), doi:10.3389/fpsyg.2013.00515

by Marco Zorzi, Alberto Testolin, Ivilin P. Stoianov

posted to bayesian deep-learning mirror-neurons by vankov on 2016-05-22 21:10:19  along with 1 person

Abstract

 

✔ Deep Neural Networks as a Computational Model for Human Shape Sensitivity

  

PLoS Comput Biol, Vol. 12, No. 4. (28 April 2016), e1004896, doi:10.1371/journal.pcbi.1004896

by Jonas Kubilius, Stefania Bracci, Hans P. Op de Beeck

posted to caffe deep-learning image neuroscience perception by ajs625 on 2016-05-16 00:17:33 

Abstract

 

✔ Deep learning.

  

Nature, Vol. 521, No. 7553. (28 May 2015), pp. 436-444

by Yann LeCun, Yoshua Bengio, Geoffrey Hinton

posted to deep-learning by assafzar on 2016-05-15 23:08:36  along with 1 person

Abstract Notes

 

✔ Basset: Learning the regulatory code of the accessible genome with deep convolutional neural networks

  

Genome Research (03 May 2016), gr.200535.115, doi:10.1101/gr.200535.115

by David R. Kelley, Jasper Snoek, John Rinn

posted to deep-learning regulation by pickw on 2016-05-07 17:35:27 

Abstract

 

✔ Mastering the game of Go with deep neural networks and tree search

  

Nature, Vol. 529, No. 7587. (28 January 2016), pp. 484-489, doi:10.1038/nature16961

by David Silver, Aja Huang, Chris J. Maddison, et al.

posted to ai deep-learning neural-networks by vankov  on 2016-05-05 12:53:35  along with 14 people

 

✔ Deep Metric Learning via Lifted Structured Feature Embedding

  

(19 Nov 2015)

by Hyun O. Song, Yu Xiang, Stefanie Jegelka, Silvio Savarese

posted to deep-learning by angli on 2016-05-02 20:01:33 

Abstract

 

✔ Convergent Learning: Do different neural networks learn the same representations?

  

(28 Feb 2016)

by Yixuan Li, Jason Yosinski, Jeff Clune, Hod Lipson, John Hopcroft

posted to deep-learning feature image representation by ajs625 on 2016-04-28 21:34:26 

Abstract

 

✔ A Taxonomy of Deep Convolutional Neural Nets for Computer Vision

  

Frontiers in Robotics and AI, Vol. 2 (25 Jan 2016), doi:10.3389/frobt.2015.00036

by Suraj Srinivas, Ravi K. Sarvadevabhatla, Konda R. Mopuri, Nikita Prabhu, Srinivas S. S. Kruthiventi, R. Venkatesh Babu

posted to deep-learning todo vision by falex on 2016-04-27 08:44:51 

Abstract

 

✔ Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

  

(2 Mar 2015)

by Sergey Ioffe, Christian Szegedy

posted to deep-learning by hans_meine on 2016-04-24 12:24:16  along with 6 people

Abstract

 

✔ Human-level control through deep reinforcement learning

  

Nature, Vol. 518, No. 7540. (26 February 2015), pp. 529-533, doi:10.1038/nature14236

by Volodymyr Mnih, Koray Kavukcuoglu, David Silver, et al.

posted to 2015 ai deep-learning game neural-network q-learning reinforcement-learning by ddahlem  on 2016-04-22 13:37:41  along with 19 people and 2 groups

 

✔ Adding Gradient Noise Improves Learning for Very Deep Networks

  

(21 Nov 2015)

by Arvind Neelakantan, Luke Vilnis, Quoc V. Le, et al.

posted to deep-learning gradient neural-network statistical-learning by lehalle on 2016-04-10 17:54:43 

Abstract

 

The application of an ensemble of boosted Elman networks to time series prediction: a benchmark study

  

J Comput Intell, Vol. 3, No. 2. (2005), pp. 119-126

by Chee P. Lim, Wei Y. Goh

posted to arma cnn convnet deep-learning neural-network time-series by lehalle on 2016-04-06 11:13:01 

 

On the prediction of solar activity using different neural network models

  

In Annales Geophysicae, Vol. 14, No. 1. (1996)

by Francoise Fessant, Samy Bengio, Daniel Collobert

posted to arma cnn compression convnet deep-learning neural-network time-series by lehalle on 2016-04-06 11:08:01 

 

✔ Identity Mappings in Deep Residual Networks

  

(16 Mar 2016)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning dlws101 by hans_meine on 2016-04-01 21:08:03 

Abstract

 

✔ Deep Residual Learning for Image Recognition

  

(10 Dec 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning dlws101 by hans_meine on 2016-04-01 21:06:16  along with 5 people

Abstract

 

✔ Variational inference for Monte Carlo objectives

  

(22 Feb 2016)

by Andriy Mnih, Danilo J. Rezende

posted to deep-learning latent-variable machine-learning mcmc statistics variational-bayes by memming on 2016-03-25 03:19:27 

Abstract

 

✔ Discriminative Regularization for Generative Models

  

(15 Feb 2016)

by Alex Lamb, Vincent Dumoulin, Aaron Courville

posted to deep-learning math by mathkann on 2016-03-24 13:53:11 

Abstract

 

✔ The Loss Surfaces of Multilayer Networks

  

(21 Jan 2015)

by Anna Choromanska, Mikael Henaff, Michael Mathieu, Gérard B. Arous, Yann LeCun

posted to deep-learning optimization by lehalle on 2016-03-24 09:55:07  along with 2 people

Abstract

 

✔ Explicit information for category-orthogonal object properties increases along the ventral stream

  

Nat Neurosci, Vol. advance online publication (22 February 2016), doi:10.1038/nn.4247

by Ha Hong, Daniel L. K. Yamins, Najib J. Majaj, James J. DiCarlo

posted to convolutional-model deep-learning it object-recognition ventral-stream by memming on 2016-03-21 20:40:19 

 

✔ Deep learning in neural networks: An overview

  

Neural Networks, Vol. 61 (8 January 2015), pp. 85-117, doi:10.1016/j.neunet.2014.09.003

by Jürgen Schmidhuber

posted to deep-learning review by pickw  on 2016-03-15 01:17:12  along with 10 people and 1 group

Abstract

 

✔ Spatio-Temporal Signatures to Predict Retinal Disease Recurrence

  

In Information Processing in Medical Imaging, Vol. 9123 (2015), pp. 152-163, doi:10.1007/978-3-319-19992-4_12

by Wolf-Dieter Vogl, SebastianM Waldstein, BiancaS Gerendas, et al.

edited by Sebastien Ourselin, Daniel C. Alexander, Carl-Fredrik Westin, M. Jorge Cardoso

posted to deep-learning by hans_meine on 2016-03-14 16:14:24 

 

✔ Learning Physical Intuition of Block Towers by Example

  

(3 Mar 2016)

by Adam Lerer, Sam Gross, Rob Fergus

posted to ai deep-learning games by mathkann on 2016-03-10 06:53:40 

Abstract

 

✔ Dynamic Memory Networks for Visual and Textual Question Answering

  

(4 Mar 2016)

by Caiming Xiong, Stephen Merity, Richard Socher

posted to ai deep-learning neural-networks by mathkann on 2016-03-09 07:18:36  along with 1 person

Abstract

 

✔ Mapping visual features to semantic profiles for retrieval in medical imaging

  

In Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on (June 2015), pp. 457-465, doi:10.1109/cvpr.2015.7298643

by Johannes Hofmanninger, Georg Langs

posted to deep-learning by hans_meine on 2016-03-04 13:28:46 

 

✔ Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets

  

(1 Jun 2015)

by Armand Joulin, Tomas Mikolov

posted to deep-learning model sequence todo by falex on 2016-03-01 15:30:14  along with 2 people

Abstract

 

✔ Using goal-driven deep learning models to understand sensory cortex

  

Nature Neuroscience, Vol. 19, No. 3. (23 February 2016), pp. 356-365, doi:10.1038/nn.4244

by Daniel L. K. Yamins, James J. DiCarlo

posted to cortex deep-learning model todo vision by falex  on 2016-02-29 15:57:40  along with 2 people

 

✔ Black box variational inference for state space models

  

(23 Nov 2015)

by Evan Archer, Il M. Park, Lars Buesing, John Cunningham, Liam Paninski

posted to deep-learning machine-learning stochastic-gradient-descent-algorithm time-series variational-bayes by memming on 2016-02-23 15:24:40 

Abstract

 

✔ Dropout: A Simple Way to Prevent Neural Networks from Overfitting

  

J. Mach. Learn. Res., Vol. 15, No. 1. (January 2014), pp. 1929-1958

by Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, Ruslan Salakhutdinov

posted to deep-learning neural-network statistical-learning by martinzokov  on 2016-02-20 01:00:47  along with 4 people and 1 group

Abstract

 

✔ Practical recommendations for gradient-based training of deep architectures

  

(16 Sep 2012)

by Yoshua Bengio

posted to deep-learning statistical-learning by lehalle on 2016-02-12 22:02:07  along with 3 people

Abstract

 

✔ Exploring the Limits of Language Modeling

  

(11 Feb 2016)

by Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, Yonghui Wu

posted to deep-learning nlp rnn by mathkann on 2016-02-09 12:22:03  along with 3 people

Abstract

 

✔ The Ebb and Flow of Deep Learning: a Theory of Local Learning

  

(22 Jun 2015)

by Pierre Baldi, Peter Sadowski

posted to deep-learning local-learning-rule machine-learning theoretical-neuroscience by memming on 2016-01-13 16:31:15 

Abstract

 

✔ Continuous control with deep reinforcement learning

  

(7 Jan 2016)

by Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, et al.

posted to continuous-control deep-learning model-based-rl reinforcement by memming on 2016-01-09 15:00:17  along with 2 people

Abstract

 

✔ Deep Learning for Content-Based Image Retrieval: A Comprehensive Study

  

In Proceedings of the 22Nd ACM International Conference on Multimedia (2014), pp. 157-166, doi:10.1145/2647868.2654948

by Ji Wan, Dayong Wang, Steven Chu Hong Hoi, et al.

posted to cbir deep-learning machine-learning review by ajs625 on 2016-01-07 20:54:41 

Abstract

 

✔ Deep learning of binary hash codes for fast image retrieval

  

In Computer Vision and Pattern Recognition Workshops (CVPRW), 2015 IEEE Conference on (June 2015), pp. 27-35, doi:10.1109/cvprw.2015.7301269

by Kevin Lin, Huei-Fang Yang, Jen-Hao Hsiao, Chu-Song Chen

posted to cbir deep-learning hashing image by ajs625 on 2016-01-07 20:52:02 

 

✔ Object Detectors Emerge in Deep Scene CNNs

  

(15 Apr 2015)

by Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba

posted to computer-vision deep-learning by assafzar on 2015-12-30 15:47:11 

Abstract

 

✔ Automatic detection of cell divisions (mitosis) in live-imaging microscopy images using Convolutional Neural Networks

  

In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (August 2015), pp. 743-746, doi:10.1109/embc.2015.7318469

by Anat Shkolyar, Amit Gefen, Dafna Benayahu, Hayit Greenspan

posted to collective-cell-migration deep-learning by assafzar on 2015-12-30 15:39:03 

 

✔ Imagenet classification with deep convolutional neural networks

  

In Advances in Neural Information Processing Systems, Vol. 25 (2012)

by Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton

posted to classification cnn cv deep-learning imagenet by ok1zjf on 2015-12-29 03:33:17 / along with 9 people

Abstract

 

✔ Learning Visual Predictive Models of Physics for Playing Billiards

  

(23 Nov 2015)

by Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, Jitendra Malik

posted to computer-vision deep-learning iclr machine-learning physics video by memming on 2015-12-22 21:14:30 

Abstract

 

✔ Stacked Attention Networks for Image Question Answering

  

(7 Nov 2015)

by Zichao Yang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Smola

posted to deep-learning image machine-learning machine-teaching speech by ajs625 on 2015-12-18 22:04:42 

Abstract

 

✔ Learning deep dynamical models from image pixels

  

(28 Oct 2014)

by Niklas Wahlström, Thomas B. Schön, Marc P. Deisenroth

posted to autoencoder deep-learning image latent-dynamics nonlinear-systems time-series video by memming on 2015-12-16 16:40:37 

Abstract

 

✔ Hierarchical Variational Models

  

(7 Nov 2015)

by Rajesh Ranganath, Dustin Tran, David M. Blei

posted to bayesian deep-learning inference-network machine-learning variational-bayes by memming on 2015-12-16 16:27:08  along with 1 person

Abstract

 

✔ Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

  

(7 Jan 2016)

by Alec Radford, Luke Metz, Soumith Chintala

posted to adversarial-network cnn deep-learning iclr image by memming on 2015-12-16 16:21:20  along with 3 people

Abstract

 

✔ Variational Auto-encoded Deep Gaussian Processes

  

(19 Nov 2015)

by Zhenwen Dai, Andreas Damianou, Javier González, Neil Lawrence

posted to autoencoder deep-gaussian-processes deep-learning gaussian-process iclr variational-bayes by memming on 2015-12-16 16:19:20 

Abstract

 

✔ Stochastic Optimization for Deep CCA via Nonlinear Orthogonal Iterations

  

(7 Oct 2015)

by Weiran Wang, Raman Arora, Karen Livescu, Nathan Srebro

posted to cca deep-learning by memming on 2015-12-16 15:55:15 

Abstract

 

✔ Why are deep nets reversible: A simple theory, with implications for training

  

(19 Nov 2015)

by Sanjeev Arora, Yingyu Liang, Tengyu Ma

posted to autoencoder deep-learning learning symmetry theoretical-neuroscience by memming on 2015-12-16 15:52:40 

Abstract

 

✔ Deep multi-scale video prediction beyond mean square error

  

(23 Nov 2015)

by Michael Mathieu, Camille Couprie, Yann LeCun

posted to deep-learning machine-learning time-series video by memming on 2015-12-16 15:31:55 

Abstract

续

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""

  

In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933

by Vincent Michalski, Roland Memisevic, Kishore Konda

edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger

posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43 

 

✔ Unsupervised Learning of Video Representations using LSTMs

  

(31 Mar 2015)

by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54  along with 4 people

Abstract

 

✔ Better Computer Go Player with Neural Network and Long-term Prediction

  

(26 Jan 2016)

by Yuandong Tian, Yan Zhu

posted to deep-learning games go by lehalle on 2015-12-09 17:57:52  along with 2 people

Abstract

 

✔ Fully Convolutional Networks for Semantic Segmentation

  

(8 Mar 2015)

by Jonathan Long, Evan Shelhamer, Trevor Darrell

posted to deep-learning by hans_meine on 2015-12-04 19:12:45  along with 2 people

Abstract Notes

 

✔ Gradient Estimation Using Stochastic Computation Graphs

  

(13 Nov 2015)

by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 

Abstract

 

✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling

  

(23 Sep 2015)

by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 

Abstract

 

✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

  

(20 Nov 2015)

by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller

posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21  along with 1 person

Abstract

 

✔ Variational Gaussian Process

  

(20 Nov 2015)

by Dustin Tran, Rajesh Ranganath, David M. Blei

posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08  along with 1 person

Abstract

 

✔ SparkNet: Training Deep Networks in Spark

  

(26 Nov 2015)

by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan

posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30  along with 3 people

Abstract

 

✔ Deep Kalman Filters

  

(16 Nov 2015)

by Rahul G. Krishnan, Uri Shalit, David Sontag

posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 

Abstract

 

✔ Sequence to Sequence Learning with Neural Networks

  

(14 Dec 2014)

by Ilya Sutskever, Oriol Vinyals, Quoc V. Le

posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05  along with 4 people

Abstract

 

✔ Privacy-Preserving Deep Learning

  

In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687

by Reza Shokri, Vitaly Shmatikov

posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 

Abstract

 

✔ Predicting effects of noncoding variants with deep learning–based sequence model

  

Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547

by Jian Zhou, Olga G. Troyanskaya

posted to deep-learning functional-annotation non-coding by pickw  on 2015-10-14 19:08:24  along with 8 people and 1 group

 

✔ Curriculum Learning

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380

by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston

posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12  along with 2 people

Abstract

 

✔ High-order neural networks and kernel methods for peptide-MHC binding prediction

  

Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371

by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein

posted to deep-learning interaction machine-learning protein-protein by ajs625  on 2015-09-22 05:37:13  along with 1 person and 1 group

Abstract

 

✔ Deep Broad Learning - Big Models for Big Data

  

(4 Sep 2015)

by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean

posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 

Abstract

 

✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

  

Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838

by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey

posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03  along with 1 person

Abstract

 

✔ A Neural Algorithm of Artistic Style

  

(2 Sep 2015)

by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59  along with 5 people

Abstract

 

✔ Quantum Deep Learning

  

(22 May 2015)

by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45  along with 2 people

Abstract

 

✔ Deep Learning for Single-View Instance Recognition

  

(29 Jul 2015)

by David Held, Sebastian Thrun, Silvio Savarese

posted to deep-learning by noud88 on 2015-07-31 13:49:47 

Abstract

 

✔ Training Very Deep Networks

  

(22 Jul 2015)

by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber

posted to deep-learning by mathkann on 2015-07-23 09:30:53 

Abstract

 

✔ Unsupervised Learning on Neural Network Outputs

  

(7 Jul 2015)

by Yao Lu

posted to deep-learning by mathkann on 2015-07-08 14:23:44 

Abstract

 

✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

  

(29 May 2015)

by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu

posted to deep-learning by hukkinen on 2015-06-16 16:12:14 

Abstract

 

✔ Variational Inference with Normalizing Flows

  

In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538

by Danilo J. Rezende, Shakir Mohamed

posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 

Abstract

 

✔ Visualizing and Understanding Recurrent Networks

  

(17 Nov 2015)

by Andrej Karpathy, Justin Johnson, Li Fei-Fei

posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34  along with 2 people

Abstract

 

✔ A Critical Review of Recurrent Neural Networks for Sequence Learning

  

(29 Jun 2015)

by Zachary C. Lipton

posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02  along with 3 people

Abstract

 

✔ Blocks and Fuel: Frameworks for deep learning

  

(1 Jun 2015)

by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al.

posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 

Abstract

 

Deep AutoRegressive Networks

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250

by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

edited by Tony Jebara, Eric P. Xing

posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

In In International Conference on Machine Learning, 2012. 103

by Quoc V. Le, Rajat Monga, Matthieu Devin, et al.

posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 

Abstract

 

✔ Reducing the dimensionality of data with neural networks.

  

Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647

by G. E. Hinton, R. R. Salakhutdinov

posted to deep-learning machine-learning print by falex  on 2015-05-12 10:18:44  along with 50 people and 10 groups

Abstract

 

✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

  

(6 Feb 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning by mathkann  on 2015-05-06 05:03:15  along with 3 people and 1 group

Abstract

 

✔ Low precision storage for deep learning

  

(3 Apr 2015)

by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David

posted to deep-learning by mathkann on 2015-04-29 19:36:28  along with 1 person

Abstract

 

✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

  

J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n

by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

posted to deep-learning by babakap on 2015-04-16 20:09:14 

Abstract

 

Theano: a CPU and GPU Math Expression Compiler

  

In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010)

by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al.

posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58  along with 1 person

Abstract

 

✔ Theano: new features and speed improvements

  

(23 Nov 2012)

by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al.

posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34  along with 3 people

Abstract

 

✔ Generative models for discovering sparse distributed representations

  

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101

by Geoffrey E. Hinton, Zoubin Ghahramani

posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19  along with 4 people

Abstract

 

✔ On the Computational Efficiency of Training Neural Networks

  

(28 Oct 2014)

by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36  along with 3 people

Abstract

 

✔ Reweighted Wake-Sleep

  

(11 Jun 2014)

by Jörg Bornschein, Yoshua Bengio

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07  along with 1 person

Abstract

 

✔ Learning Stochastic Recurrent Networks

  

(5 Mar 2015)

by Justin Bayer, Christian Osendorfer

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42  along with 3 people

Abstract

 

✔ Towards Biologically Plausible Deep Learning

  

(14 Feb 2015)

by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15  along with 2 people

Abstract

 

✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

  

(31 Aug 2007)

by Juergen Schmidhuber

posted to agi deep-learning by chadwcarlson  on 2015-04-12 11:17:52  along with 5 people and 1 group

Abstract

 

✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

  

(5 Sep 2007)

by Juergen Schmidhuber

posted to deep-learning machine-learning by chadwcarlson  on 2015-04-12 11:17:21  along with 5 people and 2 groups

Abstract

 

✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence

  

Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3

by Tom Schaul, Leo Pape, Tobias Glasmachers, et al.

edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40  along with 1 person

Abstract

 

✔ Visualizing and Understanding Convolutional Networks

  

(28 Nov 2013)

by Matthew D. Zeiler, Rob Fergus

posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group

Abstract

 

✔ Greedy layer-wise training of deep networks

  

In In NIPS (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec

posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54  along with 10 people

Abstract

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

Journal of Machine Learning Research

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53  along with 9 people and 1 group

Abstract

 

✔ Deep learning from temporal coherence in video

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469

by Hossein Mobahi, Ronan Collobert, Jason Weston

posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35  along with 5 people

Abstract

 

✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

  

(7 Apr 2015)

by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47  along with 1 person

Abstract

 

✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

  

Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806

by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al.

posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw  on 2015-04-08 03:47:39  along with 22 people and 3 groups

Abstract

 

✔ Computational intelligence techniques in bioinformatics.

  

Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47

by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali

posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 

Abstract

Tag deep-learning [159 articles] 

Recent papers classified by the tag deep-learning.

     

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""

  

In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933

by Vincent Michalski, Roland Memisevic, Kishore Konda

edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger

posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43 

 

✔ Unsupervised Learning of Video Representations using LSTMs

  

(31 Mar 2015)

by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54  along with 4 people

Abstract

 

✔ Better Computer Go Player with Neural Network and Long-term Prediction

  

(26 Jan 2016)

by Yuandong Tian, Yan Zhu

posted to deep-learning games go by lehalle on 2015-12-09 17:57:52  along with 2 people

Abstract

 

✔ Fully Convolutional Networks for Semantic Segmentation

  

(8 Mar 2015)

by Jonathan Long, Evan Shelhamer, Trevor Darrell

posted to deep-learning by hans_meine on 2015-12-04 19:12:45  along with 2 people

Abstract Notes

 

✔ Gradient Estimation Using Stochastic Computation Graphs

  

(13 Nov 2015)

by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 

Abstract

 

✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling

  

(23 Sep 2015)

by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 

Abstract

 

✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

  

(20 Nov 2015)

by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller

posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21  along with 1 person

Abstract

 

✔ Variational Gaussian Process

  

(20 Nov 2015)

by Dustin Tran, Rajesh Ranganath, David M. Blei

posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08  along with 1 person

Abstract

 

✔ SparkNet: Training Deep Networks in Spark

  

(26 Nov 2015)

by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan

posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30  along with 3 people

Abstract

 

✔ Deep Kalman Filters

  

(16 Nov 2015)

by Rahul G. Krishnan, Uri Shalit, David Sontag

posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 

Abstract

 

✔ Sequence to Sequence Learning with Neural Networks

  

(14 Dec 2014)

by Ilya Sutskever, Oriol Vinyals, Quoc V. Le

posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05  along with 4 people

Abstract

 

✔ Privacy-Preserving Deep Learning

  

In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687

by Reza Shokri, Vitaly Shmatikov

posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 

Abstract

 

✔ Predicting effects of noncoding variants with deep learning–based sequence model

  

Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547

by Jian Zhou, Olga G. Troyanskaya

posted to deep-learning functional-annotation non-coding by pickw  on 2015-10-14 19:08:24  along with 8 people and 1 group

 

✔ Curriculum Learning

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380

by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston

posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12  along with 2 people

Abstract

 

✔ High-order neural networks and kernel methods for peptide-MHC binding prediction

  

Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371

by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein

posted to deep-learning interaction machine-learning protein-protein by ajs625  on 2015-09-22 05:37:13  along with 1 person and 1 group

Abstract

 

✔ Deep Broad Learning - Big Models for Big Data

  

(4 Sep 2015)

by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean

posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 

Abstract

 

✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

  

Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838

by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey

posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03  along with 1 person

Abstract

 

✔ A Neural Algorithm of Artistic Style

  

(2 Sep 2015)

by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59  along with 5 people

Abstract

 

✔ Quantum Deep Learning

  

(22 May 2015)

by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45  along with 2 people

Abstract

 

✔ Deep Learning for Single-View Instance Recognition

  

(29 Jul 2015)

by David Held, Sebastian Thrun, Silvio Savarese

posted to deep-learning by noud88 on 2015-07-31 13:49:47 

Abstract

 

✔ Training Very Deep Networks

  

(22 Jul 2015)

by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber

posted to deep-learning by mathkann on 2015-07-23 09:30:53 

Abstract

 

✔ Unsupervised Learning on Neural Network Outputs

  

(7 Jul 2015)

by Yao Lu

posted to deep-learning by mathkann on 2015-07-08 14:23:44 

Abstract

 

✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

  

(29 May 2015)

by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu

posted to deep-learning by hukkinen on 2015-06-16 16:12:14 

Abstract

 

✔ Variational Inference with Normalizing Flows

  

In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538

by Danilo J. Rezende, Shakir Mohamed

posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 

Abstract

 

✔ Visualizing and Understanding Recurrent Networks

  

(17 Nov 2015)

by Andrej Karpathy, Justin Johnson, Li Fei-Fei

posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34  along with 2 people

Abstract

 

✔ A Critical Review of Recurrent Neural Networks for Sequence Learning

  

(29 Jun 2015)

by Zachary C. Lipton

posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02  along with 3 people

Abstract

 

✔ Blocks and Fuel: Frameworks for deep learning

  

(1 Jun 2015)

by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al.

posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 

Abstract

 

Deep AutoRegressive Networks

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250

by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

edited by Tony Jebara, Eric P. Xing

posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

In In International Conference on Machine Learning, 2012. 103

by Quoc V. Le, Rajat Monga, Matthieu Devin, et al.

posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 

Abstract

 

✔ Reducing the dimensionality of data with neural networks.

  

Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647

by G. E. Hinton, R. R. Salakhutdinov

posted to deep-learning machine-learning print by falex  on 2015-05-12 10:18:44  along with 50 people and 10 groups

Abstract

 

✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

  

(6 Feb 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning by mathkann  on 2015-05-06 05:03:15  along with 3 people and 1 group

Abstract

 

✔ Low precision storage for deep learning

  

(3 Apr 2015)

by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David

posted to deep-learning by mathkann on 2015-04-29 19:36:28  along with 1 person

Abstract

 

✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

  

J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n

by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

posted to deep-learning by babakap on 2015-04-16 20:09:14 

Abstract

 

Theano: a CPU and GPU Math Expression Compiler

  

In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010)

by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al.

posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58  along with 1 person

Abstract

 

✔ Theano: new features and speed improvements

  

(23 Nov 2012)

by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al.

posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34  along with 3 people

Abstract

 

✔ Generative models for discovering sparse distributed representations

  

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101

by Geoffrey E. Hinton, Zoubin Ghahramani

posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19  along with 4 people

Abstract

 

✔ On the Computational Efficiency of Training Neural Networks

  

(28 Oct 2014)

by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36  along with 3 people

Abstract

 

✔ Reweighted Wake-Sleep

  

(11 Jun 2014)

by Jörg Bornschein, Yoshua Bengio

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07  along with 1 person

Abstract

 

✔ Learning Stochastic Recurrent Networks

  

(5 Mar 2015)

by Justin Bayer, Christian Osendorfer

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42  along with 3 people

Abstract

 

✔ Towards Biologically Plausible Deep Learning

  

(14 Feb 2015)

by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15  along with 2 people

Abstract

 

✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

  

(31 Aug 2007)

by Juergen Schmidhuber

posted to agi deep-learning by chadwcarlson  on 2015-04-12 11:17:52  along with 5 people and 1 group

Abstract

 

✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

  

(5 Sep 2007)

by Juergen Schmidhuber

posted to deep-learning machine-learning by chadwcarlson  on 2015-04-12 11:17:21  along with 5 people and 2 groups

Abstract

 

✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence

  

Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3

by Tom Schaul, Leo Pape, Tobias Glasmachers, et al.

edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40  along with 1 person

Abstract

 

✔ Visualizing and Understanding Convolutional Networks

  

(28 Nov 2013)

by Matthew D. Zeiler, Rob Fergus

posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group

Abstract

 

✔ Greedy layer-wise training of deep networks

  

In In NIPS (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec

posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54  along with 10 people

Abstract

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

Journal of Machine Learning Research

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53  along with 9 people and 1 group

Abstract

 

✔ Deep learning from temporal coherence in video

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469

by Hossein Mobahi, Ronan Collobert, Jason Weston

posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35  along with 5 people

Abstract

 

✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

  

(7 Apr 2015)

by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47  along with 1 person

Abstract

 

✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

  

Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806

by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al.

posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw  on 2015-04-08 03:47:39  along with 22 people and 3 groups

Abstract

 

✔ Computational intelligence techniques in bioinformatics.

  

Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47

by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali

posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 

Abstract

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""

  

In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933

by Vincent Michalski, Roland Memisevic, Kishore Konda

edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger

posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43 

 

✔ Unsupervised Learning of Video Representations using LSTMs

  

(31 Mar 2015)

by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54  along with 4 people

Abstract

 

✔ Better Computer Go Player with Neural Network and Long-term Prediction

  

(26 Jan 2016)

by Yuandong Tian, Yan Zhu

posted to deep-learning games go by lehalle on 2015-12-09 17:57:52  along with 2 people

Abstract

 

✔ Fully Convolutional Networks for Semantic Segmentation

  

(8 Mar 2015)

by Jonathan Long, Evan Shelhamer, Trevor Darrell

posted to deep-learning by hans_meine on 2015-12-04 19:12:45  along with 2 people

Abstract Notes

 

✔ Gradient Estimation Using Stochastic Computation Graphs

  

(13 Nov 2015)

by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 

Abstract

 

✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling

  

(23 Sep 2015)

by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 

Abstract

 

✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

  

(20 Nov 2015)

by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller

posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21  along with 1 person

Abstract

 

✔ Variational Gaussian Process

  

(20 Nov 2015)

by Dustin Tran, Rajesh Ranganath, David M. Blei

posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08  along with 1 person

Abstract

 

✔ SparkNet: Training Deep Networks in Spark

  

(26 Nov 2015)

by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan

posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30  along with 3 people

Abstract

 

✔ Deep Kalman Filters

  

(16 Nov 2015)

by Rahul G. Krishnan, Uri Shalit, David Sontag

posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 

Abstract

 

✔ Sequence to Sequence Learning with Neural Networks

  

(14 Dec 2014)

by Ilya Sutskever, Oriol Vinyals, Quoc V. Le

posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05  along with 4 people

Abstract

 

✔ Privacy-Preserving Deep Learning

  

In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687

by Reza Shokri, Vitaly Shmatikov

posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 

Abstract

 

✔ Predicting effects of noncoding variants with deep learning–based sequence model

  

Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547

by Jian Zhou, Olga G. Troyanskaya

posted to deep-learning functional-annotation non-coding by pickw  on 2015-10-14 19:08:24  along with 8 people and 1 group

 

✔ Curriculum Learning

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380

by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston

posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12  along with 2 people

Abstract

 

✔ High-order neural networks and kernel methods for peptide-MHC binding prediction

  

Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371

by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein

posted to deep-learning interaction machine-learning protein-protein by ajs625  on 2015-09-22 05:37:13  along with 1 person and 1 group

Abstract

 

✔ Deep Broad Learning - Big Models for Big Data

  

(4 Sep 2015)

by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean

posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 

Abstract

 

✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

  

Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838

by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey

posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03  along with 1 person

Abstract

 

✔ A Neural Algorithm of Artistic Style

  

(2 Sep 2015)

by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59  along with 5 people

Abstract

 

✔ Quantum Deep Learning

  

(22 May 2015)

by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45  along with 2 people

Abstract

 

✔ Deep Learning for Single-View Instance Recognition

  

(29 Jul 2015)

by David Held, Sebastian Thrun, Silvio Savarese

posted to deep-learning by noud88 on 2015-07-31 13:49:47 

Abstract

 

✔ Training Very Deep Networks

  

(22 Jul 2015)

by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber

posted to deep-learning by mathkann on 2015-07-23 09:30:53 

Abstract

 

✔ Unsupervised Learning on Neural Network Outputs

  

(7 Jul 2015)

by Yao Lu

posted to deep-learning by mathkann on 2015-07-08 14:23:44 

Abstract

 

✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

  

(29 May 2015)

by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu

posted to deep-learning by hukkinen on 2015-06-16 16:12:14 

Abstract

 

✔ Variational Inference with Normalizing Flows

  

In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538

by Danilo J. Rezende, Shakir Mohamed

posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 

Abstract

 

✔ Visualizing and Understanding Recurrent Networks

  

(17 Nov 2015)

by Andrej Karpathy, Justin Johnson, Li Fei-Fei

posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34  along with 2 people

Abstract

 

✔ A Critical Review of Recurrent Neural Networks for Sequence Learning

  

(29 Jun 2015)

by Zachary C. Lipton

posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02  along with 3 people

Abstract

 

✔ Blocks and Fuel: Frameworks for deep learning

  

(1 Jun 2015)

by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al.

posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 

Abstract

 

Deep AutoRegressive Networks

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250

by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

edited by Tony Jebara, Eric P. Xing

posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

In In International Conference on Machine Learning, 2012. 103

by Quoc V. Le, Rajat Monga, Matthieu Devin, et al.

posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 

Abstract

 

✔ Reducing the dimensionality of data with neural networks.

  

Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647

by G. E. Hinton, R. R. Salakhutdinov

posted to deep-learning machine-learning print by falex  on 2015-05-12 10:18:44  along with 50 people and 10 groups

Abstract

 

✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

  

(6 Feb 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning by mathkann  on 2015-05-06 05:03:15  along with 3 people and 1 group

Abstract

 

✔ Low precision storage for deep learning

  

(3 Apr 2015)

by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David

posted to deep-learning by mathkann on 2015-04-29 19:36:28  along with 1 person

Abstract

 

✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

  

J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n

by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

posted to deep-learning by babakap on 2015-04-16 20:09:14 

Abstract

 

Theano: a CPU and GPU Math Expression Compiler

  

In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010)

by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al.

posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58  along with 1 person

Abstract

 

✔ Theano: new features and speed improvements

  

(23 Nov 2012)

by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al.

posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34  along with 3 people

Abstract

 

✔ Generative models for discovering sparse distributed representations

  

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101

by Geoffrey E. Hinton, Zoubin Ghahramani

posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19  along with 4 people

Abstract

 

✔ On the Computational Efficiency of Training Neural Networks

  

(28 Oct 2014)

by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36  along with 3 people

Abstract

 

✔ Reweighted Wake-Sleep

  

(11 Jun 2014)

by Jörg Bornschein, Yoshua Bengio

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07  along with 1 person

Abstract

 

✔ Learning Stochastic Recurrent Networks

  

(5 Mar 2015)

by Justin Bayer, Christian Osendorfer

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42  along with 3 people

Abstract

 

✔ Towards Biologically Plausible Deep Learning

  

(14 Feb 2015)

by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15  along with 2 people

Abstract

 

✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

  

(31 Aug 2007)

by Juergen Schmidhuber

posted to agi deep-learning by chadwcarlson  on 2015-04-12 11:17:52  along with 5 people and 1 group

Abstract

 

✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

  

(5 Sep 2007)

by Juergen Schmidhuber

posted to deep-learning machine-learning by chadwcarlson  on 2015-04-12 11:17:21  along with 5 people and 2 groups

Abstract

 

✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence

  

Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3

by Tom Schaul, Leo Pape, Tobias Glasmachers, et al.

edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40  along with 1 person

Abstract

 

✔ Visualizing and Understanding Convolutional Networks

  

(28 Nov 2013)

by Matthew D. Zeiler, Rob Fergus

posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group

Abstract

 

✔ Greedy layer-wise training of deep networks

  

In In NIPS (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec

posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54  along with 10 people

Abstract

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

Journal of Machine Learning Research

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53  along with 9 people and 1 group

Abstract

 

✔ Deep learning from temporal coherence in video

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469

by Hossein Mobahi, Ronan Collobert, Jason Weston

posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35  along with 5 people

Abstract

 

✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

  

(7 Apr 2015)

by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47  along with 1 person

Abstract

 

✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

  

Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806

by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al.

posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw  on 2015-04-08 03:47:39  along with 22 people and 3 groups

Abstract

 

✔ Computational intelligence techniques in bioinformatics.

  

Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47

by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali

posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 

Abstract

Tag deep-learning [159 articles] 

Recent papers classified by the tag deep-learning.

     

✔ Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

  

(19 Feb 2014)

by Andrew M. Saxe, James L. McClelland, Surya Ganguli

posted to deep-learning dynamical-system machine-learning optimization by memming on 2015-03-22 21:30:05 

Abstract

 

✔ DRAW: A Recurrent Neural Network For Image Generation

  

(20 May 2015)

by Karol Gregor, Ivo Danihelka, Alex Graves, Danilo J. Rezende, Daan Wierstra

posted to deep-learning by mathkann on 2015-03-21 04:25:29  along with 4 people

Abstract

 

✔ An exact mapping between the Variational Renormalization Group and Deep Learning

  

(14 Oct 2014)

by Pankaj Mehta, David J. Schwab

posted to deep-learning machine-learning physics renormalization-group by memming on 2015-03-20 18:27:55  along with 3 people

Abstract

 

✔ Complexity of random smooth functions on the high-dimensional sphere

  

The Annals of Probability, Vol. 41, No. 6. (16 Dec 2013), pp. 4214-4247, doi:10.1214/13-aop862

by Antonio Auffinger, Gerard B. Arous

posted to deep-learning high-dimension machine-learning statistics by memming on 2015-03-20 16:17:30 

Abstract

 

Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream

  

In Advances in Neural Information Processing Systems 26 (2013), pp. 3093-3101

by Daniel L. Yamins, Ha Hong, Charles Cadieu, James J. DiCarlo

edited by C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, K. Q. Weinberger

posted to convolutional-neural-network deep-learning by memming on 2015-03-10 20:15:21  along with 1 person

 

Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures

  

In Proceedings of the 30th International Conference on Machine Learning, {ICML} 2013, Atlanta, GA, USA, 16-21 June 2013 (2013), pp. 115-123

by James Bergstra, Daniel Yamins, David D. Cox

posted to deep-learning optimization by memming on 2015-03-10 20:04:49 

 

✔ Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project

  

Drug Discovery Today, Vol. 20, No. 5. (May 2015), pp. 505-513, doi:10.1016/j.drudis.2014.12.014

by Bie Verbist, Günter Klambauer, Liesbet Vervoort, et al.

posted to deep-learning drug-discovery by mathkann  on 2015-02-20 14:56:42  along with 2 people

Abstract

 

✔ Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings

  

(12 Feb 2015)

by Sanjeev Arora, Yuanzhi Li, Yingyu Liang, Tengyu Ma, Andrej Risteski

posted to deep-learning nlp by mathkann on 2015-02-18 10:03:29 

Abstract

 

✔ Multi-view Face Detection Using Deep Convolutional Neural Networks

  

(10 Feb 2015)

by Sachin S. Farfade, Mohammad Saberian, Li-Jia Li

posted to deep-learning by mathkann on 2015-02-17 14:55:40  along with 1 person

Abstract

 

✔ Large-Scale Deep Learning on the YFCC100M Dataset

  

(11 Feb 2015)

by Karl Ni, Roger Pearce, Kofi Boakye, et al.

posted to deep-learning gpu hpc by mathkann on 2015-02-14 03:05:06 

Abstract

 

✔ Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

  

(2 Apr 2015)

by Anh Nguyen, Jason Yosinski, Jeff Clune

posted to convolutional-model deep-learning image-classification by memming  on 2015-01-28 17:05:44  along with 5 people and 1 group

Abstract

 

✔ Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription

  

(27 Jun 2012)

by Nicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent

posted to deep-learning discrete latent-dynamics music by memming on 2015-01-08 21:41:48  along with 2 people

Abstract

 

✔ How to Construct Deep Recurrent Neural Networks

  

(24 Apr 2014)

by Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Yoshua Bengio

posted to deep-learning recurrent-neural-networks by raulsierra on 2014-12-17 00:36:36  along with 1 person

Abstract

 

✔ A Fast Learning Algorithm for Deep Belief Nets

  

Neural Computation, Vol. 18, No. 7. (17 May 2006), pp. 1527-1554, doi:10.1162/neco.2006.18.7.1527

by Geoffrey E. Hinton, Simon Osindero, Yee-Whye Teh

posted to deep-learning feature-learning by raulsierra on 2014-12-17 00:34:16  along with 29 people

Abstract

 

Doubly Stochastic Variational Bayes for non-Conjugate Inference

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1971-1979

by Michalis Titsias, Miguel Lázaro-gredilla

edited by Tony Jebara, Eric P. Xing

posted to deep-learning machine-learning variational-bayes by memming on 2014-12-13 17:12:17  along with 1 person

Abstract

 

✔ Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation

  

Neural Computation, Vol. 22, No. 2. (18 November 2009), pp. 511-538, doi:10.1162/neco.2009.10-08-881

by Srinivas C. Turaga, Joseph F. Murray, Viren Jain, et al.

posted to deep-learning hyperspectral-images image-segmentation by raulsierra on 2014-12-02 16:04:14  along with 4 people

Abstract

 

✔ Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion

  

J. Mach. Learn. Res., Vol. 11 (December 2010), pp. 3371-3408

by Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre A. Manzagol

posted to autoencoder deep-learning machine-learning manifold-learning unsupervised-learning by memming on 2014-11-10 15:13:25 

Abstract

 

✔ Extracting and Composing Robust Features with Denoising Autoencoders

  

In Proceedings of the 25th International Conference on Machine Learning (2008), pp. 1096-1103, doi:10.1145/1390156.1390294

by Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre A. Manzagol

posted to auto-encoder deep-learning icml manifold-learning robust by memming  on 2014-10-27 22:38:26  along with 7 people

Abstract

 

✔ Emergence of a 'visual number sense' in hierarchical generative models

  

Nat Neurosci, Vol. 15, No. 2. (8 February 2012), pp. 194-196, doi:10.1038/nn.2996

by Ivilin Stoianov, Marco Zorzi

posted to deep-learning numerosity perception by memming  on 2014-10-22 22:24:22  along with 3 people

 

Deep learning via Hessian-free optimization

  

In Proceedings of the 27th International Conference on Machine Learning (ICML-10) (June 2010), pp. 735-742

by James Martens

edited by Johannes Fürnkranz, Thorsten Joachims

posted to deep-learning hessian newton-method optimization by memming on 2014-10-19 00:44:24 

 

Generalized Denoising Auto-Encoders as Generative Models

  

In Advances in Neural Information Processing Systems 26 (2013), pp. 899-907

by Yoshua Bengio, Li Yao, Guillaume Alain, Pascal Vincent

edited by C. J. C. Burges, L. Bottou, M. Welling, Z. Ghahramani, K. Q. Weinberger

posted to auto-encoder deep-learning machine-learning robust by memming on 2014-10-19 00:23:18 

 

✔ Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

  

(10 Jun 2014)

by Yann Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio

posted to deep-learning machine-learning newton-method optimization by memming on 2014-10-19 00:01:22  along with 4 people

Abstract

 

✔ Stochastic Backpropagation and Approximate Inference in Deep Generative Models

  

In International Conference on Machine Learning (30 May 2014)

by Danilo J. Rezende, Shakir Mohamed, Daan Wierstra

posted to deep-learning machine-learning stochastic-gradient-descent-algorithm tricks variational-bayes by memming on 2014-10-12 22:12:06  along with 3 people

Abstract

 

Deep boltzmann machines

  

In International Conference on Artificial Intelligence and Statistics (2009), pp. 448-455

by Ruslan Salakhutdinov, Geoffrey E. Hinton

posted to botlzmann-machine deep-learning graph network neural-network statistica-learning by lehalle on 2014-09-26 09:32:43 

 

✔ TBCNN: A Tree-Based Convolutional Neural Network for Programming Language Processing

  

(18 Sep 2014)

by Lili Mou, Ge Li, Zhi Jin, Lu Zhang, Tao Wang

posted to deep-learning neural-networks program-analysis program-comprehension by klerisson to the group LASCAM on 2014-09-22 14:42:05 

Abstract

 

✔ Building Program Vector Representations for Deep Learning

  

(11 Sep 2014)

by Lili Mou, Ge Li, Yuxuan Liu, et al.

posted to classifier-learning deep-learning program-analysis program-comprehension by klerisson to the group LASCAM on 2014-09-17 15:37:16 

Abstract

 

✔ Unsupervised Feature Learning and Deep Learning: A Review and New Perspectives

  

(24 Jun 2012)

by Yoshua Bengio, Aaron Courville, Pascal Vincent

posted to deep-learning feature learning unsupervised by daltonwhyte on 2014-09-04 21:05:39  along with 1 person

Abstract

 

✔ Efficient Estimation of Word Representations in Vector Space

  

(7 Sep 2013)

by Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean

posted to ann bow deep-learning lm ngram skipgram by lamafan  on 2014-09-02 18:03:08 / along with 7 people

Abstract

 

✔ How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation

  

(29 Jul 2014)

by Yoshua Bengio

posted to artificial-neural-network auto-encoder deep-learning machine-learning by memming on 2014-08-14 21:16:42 

Abstract

 

✔ Improving neural networks by preventing co-adaptation of feature detectors

  

(3 Jul 2012)

by Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, Ruslan R. Salakhutdinov

posted to artificial-neural-network deep-learning machine-learning neural-network statistical-learning by lehalle on 2014-07-21 16:29:40 / along with 9 people

Abstract

 

Large scale online learning

  

Advances in neural information processing systems, Vol. 16 (2004)

by Leon B. Le Cun, L. Bottou

posted to convergence deep-learning machine-learning perceptron by lehalle on 2014-07-13 18:22:07 

 

Deep learning made easier by linear transformations in perceptrons

  

In International Conference on Artificial Intelligence and Statistics (2012), pp. 924-932

by Tapani Raiko, Harri Valpola, Yann LeCun

posted to deep-learning machine-learning perceptron by lehalle on 2014-07-13 18:19:46 

 

✔ Event-driven contrastive divergence for spiking neuromorphic systems

  

Frontiers in Neuroscience, Vol. 7 (2014), doi:10.3389/fnins.2013.00272

by Emre Neftci, Srinjoy Das, Bruno Pedroni, Kenneth Kreutz-Delgado, Gert Cauwenberghs

posted to deep-learning neuromorphic-engineering sampling-hypothesis stdp by memming on 2014-02-03 21:46:46 

 

✔ Two Distributed-State Models For Generating High-Dimensional Time Series

  

J. Mach. Learn. Res., Vol. 12 (July 2011), pp. 1025-1068

by Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis

posted to deep-learning restricted-boltzmann-machine time-series by memming on 2014-01-28 17:17:38 

Abstract

 

✔ Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 1025-1032, doi:10.1145/1553374.1553505

by Graham W. Taylor, Geoffrey E. Hinton

posted to deep-learning dynamical-system time-series by memming on 2014-01-28 17:09:04  along with 3 people

Abstract

 

✔ Automated processing and identification of benthic invertebrate samples

  

Journal of the North American Benthological Society, Vol. 29, No. 3. (8 June 2010), pp. 867-874, doi:10.1899/09-080.1

by David A. Lytle, Gonzalo Martínez-Muñoz, Wei Zhang, et al.

posted to deep-learning ecoinformatics feature-learning machine-learning by raulsierra on 2014-01-17 16:29:43 

Abstract

 

Rectified linear units improve restricted boltzmann machines

  

In Proceedings of the 27th International Conference on Machine Learning (ICML-10) (2010), pp. 807-814

by Vinod Nair, Geoffrey E. Hinton

posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:19:16 

 

Improving Deep Neural Networks for LVCSR using Rectified Linear Units and Dropout

  

In Proc. ICASSP (2013)

by George E. Dahl, Tara N. Sainath, Geoffrey E. Hinton

posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:18:24 

 

Deep learning via Hessian-free optimization

  

In Proceedings of the 27th International Conference on Machine Learning (ICML-10) (2010), pp. 735-742

by James Martens

posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:17:21 

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

J. Mach. Learn. Res., Vol. 11 (March 2010), pp. 625-660

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre A. Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:16:28  along with 3 people

Abstract

 

Greedy layer-wise training of deep networks

  

Advances in neural information processing systems, Vol. 19 (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle

posted to deep-learning machine-learning neural-network statistical-learning by lehalle on 2013-11-04 11:13:36 

 

✔ Representation Learning: A Review and New Perspectives

  

Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 35, No. 8. (August 2013), pp. 1798-1828, doi:10.1109/tpami.2013.50

by Yoshua Bengio, Aaron C. Courville, Pascal Vincent

posted to deep-learning machine-learning review todo by falex  on 2013-08-17 18:43:26  along with 4 people and 1 group

Abstract

 

✔ To Recognize Shapes, First Learn to Generate Images

  

Progress in Brain Research, Vol. 165 (2007), pp. 535-547, doi:10.1016/s0079-6123(06)65034-6

by Geoffrey E. Hinton

posted to deep-learning by tatome on 2013-08-15 01:58:43  along with 3 people

Abstract

 

✔ Feature learning and deep architectures: new directions for music informatics

  

In Journal of Intelligent Information Systems, Vol. 41, No. 3. (2013), pp. 461-481, doi:10.1007/s10844-013-0248-5

by EricJ Humphrey, JuanP Bello, Yann LeCun

posted to deep-learning by craffel on 2013-07-16 18:03:49  along with 3 people

Abstract

 

✔ Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors

  

(16 Mar 2013)

by Danqi Chen, Richard Socher, Christopher D. Manning, Andrew Y. Ng

posted to deep-learning by pengli09 on 2013-05-07 13:18:12 

Abstract

 

✔ Bayesian models: the structure of the world, uncertainty, behavior, and the brain: Bayesian models and the world

  

Annals of the New York Academy of Sciences, Vol. 1224, No. 1. (April 2011), pp. 22-39, doi:10.1111/j.1749-6632.2011.05965.x

by Iris Vilares, Konrad Kording

posted to bayesian brain deep-learning information-theory model statistics by garyfeng to the group ReadingLab on 2013-04-10 02:36:23  along with 5 people

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

(12 Jul 2012)

by Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, et al.

posted to computer_vision deep-learning feature-detection image_recognition machine-learning unsupervised-learning by tomhebbron on 2013-03-12 01:06:30  along with 11 people

Abstract

 

✔ Representation Learning: A Review and New Perspectives

  

(23 Apr 2014)

by Yoshua Bengio, Aaron Courville, Pascal Vincent

posted to deep-learning machine-learning review by tomhebbron  on 2013-03-11 19:36:25  along with 13 people and 1 group

Abstract

 

Large Scale Distributed Deep Networks

  

In Advances in Neural Information Processing Systems 25 (2012)

by Jeffrey Dea, Greg S. Corrado, Rajat Monga, et al.

posted to 2012 bfgs deep-learning deeplearning google l-nfgs lbfgs nips sgd by myui on 2012-12-07 06:10:41  along with 2 people

 

✔ Falsificationism and Statistical Learning Theory: Comparing the Popper and Vapnik-Chervonenkis Dimensions

  

Journal for General Philosophy of Science, Vol. 40, No. 1. (20 August 2009), pp. 51-58, doi:10.1007/s10838-009-9091-3

by David Corfield, Bernhard Schölkopf, Vladimir Vapnik

posted to deep-learning machine-learning philosophy-of-science statistics by tomhebbron on 2012-11-04 00:18:40  along with 1 person

Abstract

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""

  

In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933

by Vincent Michalski, Roland Memisevic, Kishore Konda

edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger

posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43 

 

✔ Unsupervised Learning of Video Representations using LSTMs

  

(31 Mar 2015)

by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54  along with 4 people

Abstract

 

✔ Better Computer Go Player with Neural Network and Long-term Prediction

  

(26 Jan 2016)

by Yuandong Tian, Yan Zhu

posted to deep-learning games go by lehalle on 2015-12-09 17:57:52  along with 2 people

Abstract

 

✔ Fully Convolutional Networks for Semantic Segmentation

  

(8 Mar 2015)

by Jonathan Long, Evan Shelhamer, Trevor Darrell

posted to deep-learning by hans_meine on 2015-12-04 19:12:45  along with 2 people

Abstract Notes

 

✔ Gradient Estimation Using Stochastic Computation Graphs

  

(13 Nov 2015)

by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 

Abstract

 

✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling

  

(23 Sep 2015)

by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 

Abstract

 

✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

  

(20 Nov 2015)

by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller

posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21  along with 1 person

Abstract

 

✔ Variational Gaussian Process

  

(20 Nov 2015)

by Dustin Tran, Rajesh Ranganath, David M. Blei

posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08  along with 1 person

Abstract

 

✔ SparkNet: Training Deep Networks in Spark

  

(26 Nov 2015)

by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan

posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30  along with 3 people

Abstract

 

✔ Deep Kalman Filters

  

(16 Nov 2015)

by Rahul G. Krishnan, Uri Shalit, David Sontag

posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 

Abstract

 

✔ Sequence to Sequence Learning with Neural Networks

  

(14 Dec 2014)

by Ilya Sutskever, Oriol Vinyals, Quoc V. Le

posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05  along with 4 people

Abstract

 

✔ Privacy-Preserving Deep Learning

  

In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687

by Reza Shokri, Vitaly Shmatikov

posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 

Abstract

 

✔ Predicting effects of noncoding variants with deep learning–based sequence model

  

Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547

by Jian Zhou, Olga G. Troyanskaya

posted to deep-learning functional-annotation non-coding by pickw  on 2015-10-14 19:08:24  along with 8 people and 1 group

 

✔ Curriculum Learning

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380

by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston

posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12  along with 2 people

Abstract

 

✔ High-order neural networks and kernel methods for peptide-MHC binding prediction

  

Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371

by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein

posted to deep-learning interaction machine-learning protein-protein by ajs625  on 2015-09-22 05:37:13  along with 1 person and 1 group

Abstract

 

✔ Deep Broad Learning - Big Models for Big Data

  

(4 Sep 2015)

by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean

posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 

Abstract

 

✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

  

Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838

by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey

posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03  along with 1 person

Abstract

 

✔ A Neural Algorithm of Artistic Style

  

(2 Sep 2015)

by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59  along with 5 people

Abstract

 

✔ Quantum Deep Learning

  

(22 May 2015)

by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45  along with 2 people

Abstract

 

✔ Deep Learning for Single-View Instance Recognition

  

(29 Jul 2015)

by David Held, Sebastian Thrun, Silvio Savarese

posted to deep-learning by noud88 on 2015-07-31 13:49:47 

Abstract

 

✔ Training Very Deep Networks

  

(22 Jul 2015)

by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber

posted to deep-learning by mathkann on 2015-07-23 09:30:53 

Abstract

 

✔ Unsupervised Learning on Neural Network Outputs

  

(7 Jul 2015)

by Yao Lu

posted to deep-learning by mathkann on 2015-07-08 14:23:44 

Abstract

 

✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

  

(29 May 2015)

by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu

posted to deep-learning by hukkinen on 2015-06-16 16:12:14 

Abstract

 

✔ Variational Inference with Normalizing Flows

  

In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538

by Danilo J. Rezende, Shakir Mohamed

posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 

Abstract

 

✔ Visualizing and Understanding Recurrent Networks

  

(17 Nov 2015)

by Andrej Karpathy, Justin Johnson, Li Fei-Fei

posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34  along with 2 people

Abstract

 

✔ A Critical Review of Recurrent Neural Networks for Sequence Learning

  

(29 Jun 2015)

by Zachary C. Lipton

posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02  along with 3 people

Abstract

 

✔ Blocks and Fuel: Frameworks for deep learning

  

(1 Jun 2015)

by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al.

posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 

Abstract

 

Deep AutoRegressive Networks

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250

by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

edited by Tony Jebara, Eric P. Xing

posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

In In International Conference on Machine Learning, 2012. 103

by Quoc V. Le, Rajat Monga, Matthieu Devin, et al.

posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 

Abstract

 

✔ Reducing the dimensionality of data with neural networks.

  

Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647

by G. E. Hinton, R. R. Salakhutdinov

posted to deep-learning machine-learning print by falex  on 2015-05-12 10:18:44  along with 50 people and 10 groups

Abstract

 

✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

  

(6 Feb 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning by mathkann  on 2015-05-06 05:03:15  along with 3 people and 1 group

Abstract

 

✔ Low precision storage for deep learning

  

(3 Apr 2015)

by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David

posted to deep-learning by mathkann on 2015-04-29 19:36:28  along with 1 person

Abstract

 

✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

  

J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n

by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

posted to deep-learning by babakap on 2015-04-16 20:09:14 

Abstract

 

Theano: a CPU and GPU Math Expression Compiler

  

In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010)

by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al.

posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58  along with 1 person

Abstract

 

✔ Theano: new features and speed improvements

  

(23 Nov 2012)

by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al.

posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34  along with 3 people

Abstract

 

✔ Generative models for discovering sparse distributed representations

  

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101

by Geoffrey E. Hinton, Zoubin Ghahramani

posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19  along with 4 people

Abstract

 

✔ On the Computational Efficiency of Training Neural Networks

  

(28 Oct 2014)

by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36  along with 3 people

Abstract

 

✔ Reweighted Wake-Sleep

  

(11 Jun 2014)

by Jörg Bornschein, Yoshua Bengio

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07  along with 1 person

Abstract

 

✔ Learning Stochastic Recurrent Networks

  

(5 Mar 2015)

by Justin Bayer, Christian Osendorfer

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42  along with 3 people

Abstract

 

✔ Towards Biologically Plausible Deep Learning

  

(14 Feb 2015)

by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15  along with 2 people

Abstract

 

✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

  

(31 Aug 2007)

by Juergen Schmidhuber

posted to agi deep-learning by chadwcarlson  on 2015-04-12 11:17:52  along with 5 people and 1 group

Abstract

 

✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

  

(5 Sep 2007)

by Juergen Schmidhuber

posted to deep-learning machine-learning by chadwcarlson  on 2015-04-12 11:17:21  along with 5 people and 2 groups

Abstract

 

✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence

  

Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3

by Tom Schaul, Leo Pape, Tobias Glasmachers, et al.

edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40  along with 1 person

Abstract

 

✔ Visualizing and Understanding Convolutional Networks

  

(28 Nov 2013)

by Matthew D. Zeiler, Rob Fergus

posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group

Abstract

 

✔ Greedy layer-wise training of deep networks

  

In In NIPS (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec

posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54  along with 10 people

Abstract

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

Journal of Machine Learning Research

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53  along with 9 people and 1 group

Abstract

 

✔ Deep learning from temporal coherence in video

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469

by Hossein Mobahi, Ronan Collobert, Jason Weston

posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35  along with 5 people

Abstract

 

✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

  

(7 Apr 2015)

by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47  along with 1 person

Abstract

 

✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

  

Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806

by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al.

posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw  on 2015-04-08 03:47:39  along with 22 people and 3 groups

Abstract

 

✔ Computational intelligence techniques in bioinformatics.

  

Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47

by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali

posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 

Abstract

Tag deep-learning [159 articles] 

Recent papers classified by the tag deep-learning.

    

 

Cooperative Learning and Soft Skills Training in an IT Course.

  

Journal of Information Technology Education, Vol. 11 (January 2012), pp. 65-79

by Aimao Zhang, Louise Spiteri

posted to collaborative-learning course-design deep-learning group-work-in-education information-technology information-technology----study-teaching-higher peer-assessment researchsoft-skills teaching-methods----research universities-colleges----curricula by jxchryst on 2012-10-24 13:18:23 

Abstract Notes

 

✔ Rapid Feature Learning with Stacked Linear Denoisers

  

(5 May 2011)

by Zhixiang E. Xu, Kilian Q. Weinberger, Fei Sha

posted to classification deep-learning machine-learning svm unsupervised-learning by tomhebbron on 2012-08-20 13:10:49 

Abstract

 

✔ Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]

  

Computational Intelligence Magazine, IEEE, Vol. 5, No. 4. (November 2010), pp. 13-18, doi:10.1109/mci.2010.938364

by Itamar Arel, Derek C. Rose, T. P. Karnowski

posted to deep-learning review by tomhebbron on 2012-06-25 20:10:22  along with 5 people

Abstract

 

✔ Learning Deep Architectures for AI

  

Foundations and Trends® in Machine Learning, Vol. 2, No. 1. (January 2009), pp. 1-127, doi:10.1561/2200000006

by Y. Bengio

posted to deep-learning machine-learning neural_network review by tomhebbron on 2012-06-25 20:03:36  along with 20 people

Abstract

 

Building high-level features using large scale unsupervised learning

  

In International Conference in Machine Learning (2012)

by Quoc Le, Marc'Aurelio Ranzato, Rajat Monga, et al.

posted to deep-learning machine-learning unsupervised-learning by tomhebbron on 2012-06-23 13:55:28 

 

✔ Deep Convolutional Networks for Scene Parsing

  

by David Grangier, Léon Bottou, Ronan Collobert

posted to convnet deep-learning scene-parsing by assad79 on 2012-05-11 12:32:03 

Abstract

 

Understanding the difficulty of training deep feedforward neural networks

  

In Proceedings of AISTATS 2010, Vol. 9 (May 2010), pp. 249-256

by Yoshua Bengio, Xavier Glorot

posted to bengio deep-learning by lmsasu on 2012-02-11 09:32:56  along with 1 person

Abstract

 

Deep learning via semi-supervised embedding

  

In Proceedings of the 25th Annual International Conference on Machine Learning (ICML 2008) (2008), pp. 1168-1175

by J. Weston, F. Ratle, R. Collobert

edited by Andrew Mccallum, Sam Roweis

posted to bib deep-learning ssl by abgoldberg on 2009-02-05 16:08:02  along with 1 person

 

Semi-supervised learning of compact document representations with deep networks

  

In Proceedings of the 25th Annual International Conference on Machine Learning (ICML 2008) (2008), pp. 792-799

by M. Ranzato, M. Szummer

edited by Andrew Mccallum, Sam Roweis

posted to bib deep-learning nlp ssl by abgoldberg on 2009-02-05 16:08:02 

from: 

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""

  

In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933

by Vincent Michalski, Roland Memisevic, Kishore Konda

edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger

posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43 

 

✔ Unsupervised Learning of Video Representations using LSTMs

  

(31 Mar 2015)

by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54  along with 4 people

Abstract

 

✔ Better Computer Go Player with Neural Network and Long-term Prediction

  

(26 Jan 2016)

by Yuandong Tian, Yan Zhu

posted to deep-learning games go by lehalle on 2015-12-09 17:57:52  along with 2 people

Abstract

 

✔ Fully Convolutional Networks for Semantic Segmentation

  

(8 Mar 2015)

by Jonathan Long, Evan Shelhamer, Trevor Darrell

posted to deep-learning by hans_meine on 2015-12-04 19:12:45  along with 2 people

Abstract Notes

 

✔ Gradient Estimation Using Stochastic Computation Graphs

  

(13 Nov 2015)

by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 

Abstract

 

✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling

  

(23 Sep 2015)

by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 

Abstract

 

✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

  

(20 Nov 2015)

by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller

posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21  along with 1 person

Abstract

 

✔ Variational Gaussian Process

  

(20 Nov 2015)

by Dustin Tran, Rajesh Ranganath, David M. Blei

posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08  along with 1 person

Abstract

 

✔ SparkNet: Training Deep Networks in Spark

  

(26 Nov 2015)

by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan

posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30  along with 3 people

Abstract

 

✔ Deep Kalman Filters

  

(16 Nov 2015)

by Rahul G. Krishnan, Uri Shalit, David Sontag

posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 

Abstract

 

✔ Sequence to Sequence Learning with Neural Networks

  

(14 Dec 2014)

by Ilya Sutskever, Oriol Vinyals, Quoc V. Le

posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05  along with 4 people

Abstract

 

✔ Privacy-Preserving Deep Learning

  

In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687

by Reza Shokri, Vitaly Shmatikov

posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 

Abstract

 

✔ Predicting effects of noncoding variants with deep learning–based sequence model

  

Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547

by Jian Zhou, Olga G. Troyanskaya

posted to deep-learning functional-annotation non-coding by pickw  on 2015-10-14 19:08:24  along with 8 people and 1 group

 

✔ Curriculum Learning

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380

by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston

posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12  along with 2 people

Abstract

 

✔ High-order neural networks and kernel methods for peptide-MHC binding prediction

  

Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371

by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein

posted to deep-learning interaction machine-learning protein-protein by ajs625  on 2015-09-22 05:37:13  along with 1 person and 1 group

Abstract

 

✔ Deep Broad Learning - Big Models for Big Data

  

(4 Sep 2015)

by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean

posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 

Abstract

 

✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

  

Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838

by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey

posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03  along with 1 person

Abstract

 

✔ A Neural Algorithm of Artistic Style

  

(2 Sep 2015)

by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59  along with 5 people

Abstract

 

✔ Quantum Deep Learning

  

(22 May 2015)

by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45  along with 2 people

Abstract

 

✔ Deep Learning for Single-View Instance Recognition

  

(29 Jul 2015)

by David Held, Sebastian Thrun, Silvio Savarese

posted to deep-learning by noud88 on 2015-07-31 13:49:47 

Abstract

 

✔ Training Very Deep Networks

  

(22 Jul 2015)

by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber

posted to deep-learning by mathkann on 2015-07-23 09:30:53 

Abstract

 

✔ Unsupervised Learning on Neural Network Outputs

  

(7 Jul 2015)

by Yao Lu

posted to deep-learning by mathkann on 2015-07-08 14:23:44 

Abstract

 

✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

  

(29 May 2015)

by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu

posted to deep-learning by hukkinen on 2015-06-16 16:12:14 

Abstract

 

✔ Variational Inference with Normalizing Flows

  

In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538

by Danilo J. Rezende, Shakir Mohamed

posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 

Abstract

 

✔ Visualizing and Understanding Recurrent Networks

  

(17 Nov 2015)

by Andrej Karpathy, Justin Johnson, Li Fei-Fei

posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34  along with 2 people

Abstract

 

✔ A Critical Review of Recurrent Neural Networks for Sequence Learning

  

(29 Jun 2015)

by Zachary C. Lipton

posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02  along with 3 people

Abstract

 

✔ Blocks and Fuel: Frameworks for deep learning

  

(1 Jun 2015)

by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al.

posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 

Abstract

 

Deep AutoRegressive Networks

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250

by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

edited by Tony Jebara, Eric P. Xing

posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

In In International Conference on Machine Learning, 2012. 103

by Quoc V. Le, Rajat Monga, Matthieu Devin, et al.

posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 

Abstract

 

✔ Reducing the dimensionality of data with neural networks.

  

Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647

by G. E. Hinton, R. R. Salakhutdinov

posted to deep-learning machine-learning print by falex  on 2015-05-12 10:18:44  along with 50 people and 10 groups

Abstract

 

✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

  

(6 Feb 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning by mathkann  on 2015-05-06 05:03:15  along with 3 people and 1 group

Abstract

 

✔ Low precision storage for deep learning

  

(3 Apr 2015)

by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David

posted to deep-learning by mathkann on 2015-04-29 19:36:28  along with 1 person

Abstract

 

✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

  

J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n

by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

posted to deep-learning by babakap on 2015-04-16 20:09:14 

Abstract

 

Theano: a CPU and GPU Math Expression Compiler

  

In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010)

by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al.

posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58  along with 1 person

Abstract

 

✔ Theano: new features and speed improvements

  

(23 Nov 2012)

by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al.

posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34  along with 3 people

Abstract

 

✔ Generative models for discovering sparse distributed representations

  

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101

by Geoffrey E. Hinton, Zoubin Ghahramani

posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19  along with 4 people

Abstract

 

✔ On the Computational Efficiency of Training Neural Networks

  

(28 Oct 2014)

by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36  along with 3 people

Abstract

 

✔ Reweighted Wake-Sleep

  

(11 Jun 2014)

by Jörg Bornschein, Yoshua Bengio

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07  along with 1 person

Abstract

 

✔ Learning Stochastic Recurrent Networks

  

(5 Mar 2015)

by Justin Bayer, Christian Osendorfer

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42  along with 3 people

Abstract

 

✔ Towards Biologically Plausible Deep Learning

  

(14 Feb 2015)

by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15  along with 2 people

Abstract

 

✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

  

(31 Aug 2007)

by Juergen Schmidhuber

posted to agi deep-learning by chadwcarlson  on 2015-04-12 11:17:52  along with 5 people and 1 group

Abstract

 

✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

  

(5 Sep 2007)

by Juergen Schmidhuber

posted to deep-learning machine-learning by chadwcarlson  on 2015-04-12 11:17:21  along with 5 people and 2 groups

Abstract

 

✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence

  

Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3

by Tom Schaul, Leo Pape, Tobias Glasmachers, et al.

edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40  along with 1 person

Abstract

 

✔ Visualizing and Understanding Convolutional Networks

  

(28 Nov 2013)

by Matthew D. Zeiler, Rob Fergus

posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group

Abstract

 

✔ Greedy layer-wise training of deep networks

  

In In NIPS (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec

posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54  along with 10 people

Abstract

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

Journal of Machine Learning Research

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53  along with 9 people and 1 group

Abstract

 

✔ Deep learning from temporal coherence in video

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469

by Hossein Mobahi, Ronan Collobert, Jason Weston

posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35  along with 5 people

Abstract

 

✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

  

(7 Apr 2015)

by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47  along with 1 person

Abstract

 

✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

  

Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806

by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al.

posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw  on 2015-04-08 03:47:39  along with 22 people and 3 groups

Abstract

 

✔ Computational intelligence techniques in bioinformatics.

  

Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47

by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali

posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 

Abstract

http://www.citeulike.org/tag/deep-learning/page/1

Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""

  

In Advances in Neural Information Processing Systems 27 (2014), pp. 1925-1933

by Vincent Michalski, Roland Memisevic, Kishore Konda

edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, K. Q. Weinberger

posted to autoencoder deep-learning lstm machine-learning nips recurrent-neural-network time-series video by memming on 2015-12-16 15:20:43 

 

✔ Unsupervised Learning of Video Representations using LSTMs

  

(31 Mar 2015)

by Nitish Srivastava, Elman Mansimov, Ruslan Salakhutdinov

posted to autoencoder deep-learning icml lstm machine-learning time-series video by memming on 2015-12-16 15:13:54  along with 4 people

Abstract

 

✔ Better Computer Go Player with Neural Network and Long-term Prediction

  

(26 Jan 2016)

by Yuandong Tian, Yan Zhu

posted to deep-learning games go by lehalle on 2015-12-09 17:57:52  along with 2 people

Abstract

 

✔ Fully Convolutional Networks for Semantic Segmentation

  

(8 Mar 2015)

by Jonathan Long, Evan Shelhamer, Trevor Darrell

posted to deep-learning by hans_meine on 2015-12-04 19:12:45  along with 2 people

Abstract Notes

 

✔ Gradient Estimation Using Stochastic Computation Graphs

  

(13 Nov 2015)

by John Schulman, Nicolas Heess, Theophane Weber, Pieter Abbeel

posted to deep-learning deep-mind machine-learning tool by memming on 2015-12-04 15:27:11 

Abstract

 

✔ Deep Temporal Sigmoid Belief Networks for Sequence Modeling

  

(23 Sep 2015)

by Zhe Gan, Chunyuan Li, Ricardo Henao, David Carlson, Lawrence Carin

posted to deep-learning hmm latent-dynamics time-series variational-bayes by memming on 2015-11-30 17:58:47 

Abstract

 

✔ Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images

  

(20 Nov 2015)

by Manuel Watter, Jost T. Springenberg, Joschka Boedecker, Martin Riedmiller

posted to deep-learning latent-dynamics linear-dynamical-system nonlinear-systems optimal-control by memming on 2015-11-30 17:40:21  along with 1 person

Abstract

 

✔ Variational Gaussian Process

  

(20 Nov 2015)

by Dustin Tran, Rajesh Ranganath, David M. Blei

posted to deep-learning gaussian-process latent-variable nonlinear variational-bayes by memming on 2015-11-26 16:28:08  along with 1 person

Abstract

 

✔ SparkNet: Training Deep Networks in Spark

  

(26 Nov 2015)

by Philipp Moritz, Robert Nishihara, Ion Stoica, Michael I. Jordan

posted to deep-learning machine-learning software spark by mathkann on 2015-11-23 17:51:30  along with 3 people

Abstract

 

✔ Deep Kalman Filters

  

(16 Nov 2015)

by Rahul G. Krishnan, Uri Shalit, David Sontag

posted to deep-learning kalman-filter stochastic-gradient-descent-algorithm by memming on 2015-11-18 21:41:24 

Abstract

 

✔ Sequence to Sequence Learning with Neural Networks

  

(14 Dec 2014)

by Ilya Sutskever, Oriol Vinyals, Quoc V. Le

posted to deep-learning nlp by mathkann on 2015-11-04 06:49:05  along with 4 people

Abstract

 

✔ Privacy-Preserving Deep Learning

  

In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security (October 2015), pp. 1310-1321, doi:10.1145/2810103.2813687

by Reza Shokri, Vitaly Shmatikov

posted to deep-learning for:yuchenzhao machine-learning neural-networks privacy by tnhh on 2015-10-15 06:58:13 

Abstract

 

✔ Predicting effects of noncoding variants with deep learning–based sequence model

  

Nature Methods, Vol. 12, No. 10. (24 August 2015), pp. 931-934, doi:10.1038/nmeth.3547

by Jian Zhou, Olga G. Troyanskaya

posted to deep-learning functional-annotation non-coding by pickw  on 2015-10-14 19:08:24  along with 8 people and 1 group

 

✔ Curriculum Learning

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 41-48, doi:10.1145/1553374.1553380

by Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston

posted to curriculum-learning deep-learning machine-learning by memming on 2015-10-07 14:30:12  along with 2 people

Abstract

 

✔ High-order neural networks and kernel methods for peptide-MHC binding prediction

  

Bioinformatics, Vol. 31, No. 22. (15 November 2015), pp. 3600-3607, doi:10.1093/bioinformatics/btv371

by Pavel P. Kuksa, Martin R. Min, Rishabh Dugar, Mark Gerstein

posted to deep-learning interaction machine-learning protein-protein by ajs625  on 2015-09-22 05:37:13  along with 1 person and 1 group

Abstract

 

✔ Deep Broad Learning - Big Models for Big Data

  

(4 Sep 2015)

by Nayyar A. Zaidi, Geoffrey I. Webb, Mark J. Carman, Francois Petitjean

posted to bias broad-learning deep-learning machine-learning by ajs625 on 2015-09-14 04:12:09 

Abstract

 

✔ Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning.

  

Nature biotechnology, Vol. 33, No. 8. (August 2015), pp. 831-838

by Babak Alipanahi, Andrew Delong, Matthew T. Weirauch, Brendan J. Frey

posted to deep-learning dna-protein interaction machine-learning rna-protein by ajs625 on 2015-09-12 22:53:03  along with 1 person

Abstract

 

✔ A Neural Algorithm of Artistic Style

  

(2 Sep 2015)

by Leon A. Gatys, Alexander S. Ecker, Matthias Bethge

posted to computer-vision deep-learning to-code visualization by mathkann on 2015-09-01 09:39:59  along with 5 people

Abstract

 

✔ Quantum Deep Learning

  

(22 May 2015)

by Nathan Wiebe, Ashish Kapoor, Krysta M. Svore

posted to ai deep-learning quantum-computing by mathkann on 2015-08-16 19:42:45  along with 2 people

Abstract

 

✔ Deep Learning for Single-View Instance Recognition

  

(29 Jul 2015)

by David Held, Sebastian Thrun, Silvio Savarese

posted to deep-learning by noud88 on 2015-07-31 13:49:47 

Abstract

 

✔ Training Very Deep Networks

  

(22 Jul 2015)

by Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber

posted to deep-learning by mathkann on 2015-07-23 09:30:53 

Abstract

 

✔ Unsupervised Learning on Neural Network Outputs

  

(7 Jul 2015)

by Yao Lu

posted to deep-learning by mathkann on 2015-07-08 14:23:44 

Abstract

 

✔ Solving Verbal Comprehension Questions in IQ Test by Knowledge-Powered Word Embedding

  

(29 May 2015)

by Huazheng Wang, Bin Gao, Jiang Bian, Fei Tian, Tie-Yan Liu

posted to deep-learning by hukkinen on 2015-06-16 16:12:14 

Abstract

 

✔ Variational Inference with Normalizing Flows

  

In Proceedings of The 32nd International Conference on Machine Learning (26 May 2015), pp. 1530-1538

by Danilo J. Rezende, Shakir Mohamed

posted to deep-learning entropy icml invertible normalizing-flows variational-bayes by memming on 2015-06-14 17:51:43 

Abstract

 

✔ Visualizing and Understanding Recurrent Networks

  

(17 Nov 2015)

by Andrej Karpathy, Justin Johnson, Li Fei-Fei

posted to deep-learning rnn by mathkann on 2015-06-10 08:48:34  along with 2 people

Abstract

 

✔ A Critical Review of Recurrent Neural Networks for Sequence Learning

  

(29 Jun 2015)

by Zachary C. Lipton

posted to deep-learning rnn by mathkann on 2015-06-03 07:28:02  along with 3 people

Abstract

 

✔ Blocks and Fuel: Frameworks for deep learning

  

(1 Jun 2015)

by Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, et al.

posted to deep-learning frameworks python by mathkann on 2015-06-02 06:21:36 

Abstract

 

Deep AutoRegressive Networks

  

In Proceedings of the 31st International Conference on Machine Learning (ICML-14) (2014), pp. 1242-1250

by Karol Gregor, Ivo Danihelka, Andriy Mnih, Charles Blundell, Daan Wierstra

edited by Tony Jebara, Eric P. Xing

posted to autoregressive deep-learning time-series by memming on 2015-05-29 23:35:44 

Abstract

 

✔ Building high-level features using large scale unsupervised learning

  

In In International Conference on Machine Learning, 2012. 103

by Quoc V. Le, Rajat Monga, Matthieu Devin, et al.

posted to deep-learning neural-networks by vankov on 2015-05-25 08:47:23 

Abstract

 

✔ Reducing the dimensionality of data with neural networks.

  

Science (New York, N.Y.), Vol. 313, No. 5786. (28 July 2006), pp. 504-507, doi:10.1126/science.1127647

by G. E. Hinton, R. R. Salakhutdinov

posted to deep-learning machine-learning print by falex  on 2015-05-12 10:18:44  along with 50 people and 10 groups

Abstract

 

✔ Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

  

(6 Feb 2015)

by Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun

posted to deep-learning by mathkann  on 2015-05-06 05:03:15  along with 3 people and 1 group

Abstract

 

✔ Low precision storage for deep learning

  

(3 Apr 2015)

by Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David

posted to deep-learning by mathkann on 2015-04-29 19:36:28  along with 1 person

Abstract

 

✔ Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

  

J. Chem. Inf. Model., Vol. 55, No. 2. (23 February 2015), pp. 263-274, doi:10.1021/ci500747n

by Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik

posted to deep-learning by babakap on 2015-04-16 20:09:14 

Abstract

 

Theano: a CPU and GPU Math Expression Compiler

  

In Proceedings of the Python for Scientific Computing Conference ({SciPy}) (June 2010)

by James Bergstra, Olivier Breuleux, Frédéric Bastien, et al.

posted to deep-learning gpu-computing machine-learning theano by chadwcarlson on 2015-04-14 15:28:58  along with 1 person

Abstract

 

✔ Theano: new features and speed improvements

  

(23 Nov 2012)

by Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, et al.

posted to deep-learning machine-learning psychophysics theano by chadwcarlson on 2015-04-14 15:27:34  along with 3 people

Abstract

 

✔ Generative models for discovering sparse distributed representations

  

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, Vol. 352, No. 1358. (29 August 1997), pp. 1177-1190, doi:10.1098/rstb.1997.0101

by Geoffrey E. Hinton, Zoubin Ghahramani

posted to deep-learning by chadwcarlson on 2015-04-12 12:04:19  along with 4 people

Abstract

 

✔ On the Computational Efficiency of Training Neural Networks

  

(28 Oct 2014)

by Roi Livni, Shai Shalev-Shwartz, Ohad Shamir

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:36  along with 3 people

Abstract

 

✔ Reweighted Wake-Sleep

  

(11 Jun 2014)

by Jörg Bornschein, Yoshua Bengio

posted to deep-learning by chadwcarlson on 2015-04-12 12:03:07  along with 1 person

Abstract

 

✔ Learning Stochastic Recurrent Networks

  

(5 Mar 2015)

by Justin Bayer, Christian Osendorfer

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:42  along with 3 people

Abstract

 

✔ Towards Biologically Plausible Deep Learning

  

(14 Feb 2015)

by Yoshua Bengio, Dong-Hyun Lee, Jorg Bornschein, Zhouhan Lin

posted to deep-learning by chadwcarlson on 2015-04-12 11:47:15  along with 2 people

Abstract

 

✔ 2006: Celebrating 75 years of AI - History and Outlook: the Next 25 Years

  

(31 Aug 2007)

by Juergen Schmidhuber

posted to agi deep-learning by chadwcarlson  on 2015-04-12 11:17:52  along with 5 people and 1 group

Abstract

 

✔ Simple Algorithmic Principles of Discovery, Subjective Beauty, Selective Attention, Curiosity & Creativity

  

(5 Sep 2007)

by Juergen Schmidhuber

posted to deep-learning machine-learning by chadwcarlson  on 2015-04-12 11:17:21  along with 5 people and 2 groups

Abstract

 

✔ Coherence Progress: A Measure of Interestingness Based on Fixed Compressors Artificial General Intelligence

  

Vol. 6830 (2011), pp. 21-30, doi:10.1007/978-3-642-22887-2_3

by Tom Schaul, Leo Pape, Tobias Glasmachers, et al.

edited by Jürgen Schmidhuber, Kristinn Thórisson, Moshe Looks, Jürgen Schmidhuber, Kristinn R. Thórisson, Moshe Looks

posted to agi deep-learning by chadwcarlson on 2015-04-12 11:15:40  along with 1 person

Abstract

 

✔ Visualizing and Understanding Convolutional Networks

  

(28 Nov 2013)

by Matthew D. Zeiler, Rob Fergus

posted to convolutional-nn deep-learning machine-learning visualization by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:04:29 along with 7 people and 1 group

Abstract

 

✔ Greedy layer-wise training of deep networks

  

In In NIPS (2007)

by Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, Université De Montréal, Montréal Québec

posted to deep-learning dnn learning neural-networks by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:01:54  along with 10 people

Abstract

 

✔ Why Does Unsupervised Pre-training Help Deep Learning?

  

Journal of Machine Learning Research

by Dumitru Erhan, Yoshua Bengio, Aaron Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio

posted to deep-learning by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 11:00:53  along with 9 people and 1 group

Abstract

 

✔ Deep learning from temporal coherence in video

  

In Proceedings of the 26th Annual International Conference on Machine Learning (2009), pp. 737-744, doi:10.1145/1553374.1553469

by Hossein Mobahi, Ronan Collobert, Jason Weston

posted to deep-learning motion by chadwcarlson to the group Machine Perception & Cognitive Robotics at FAU on 2015-04-12 10:59:35  along with 5 people

Abstract

 

✔ A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

  

(7 Apr 2015)

by Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

posted to deep-learning nonlinear-systems rectified-linear recurrent-neural-network by memming on 2015-04-09 02:29:47  along with 1 person

Abstract

 

✔ RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.

  

Science (New York, N.Y.), Vol. 347, No. 6218. (9 January 2015), 1254806, doi:10.1126/science.1254806

by Hui Y. Xiong, Babak Alipanahi, Leo J. Lee, et al.

posted to alternative-splicing deep-learning eqtl machine-learning quantitative-trait by pickw  on 2015-04-08 03:47:39  along with 22 people and 3 groups

Abstract

 

✔ Computational intelligence techniques in bioinformatics.

  

Computational biology and chemistry, Vol. 47 (December 2013), pp. 37-47

by Aboul Ella E. Hassanien, Eiman Tamah T. Al-Shammari, Neveen I. Ghali

posted to ai bioinf deep-learning fuzzy ml by guhjy on 2015-03-28 04:49:38 

Abstract