NLP之路-Deep Learning for NLP 文章列举
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From:
http://www.xperseverance.net/blogs/2013/07/2124/
慢慢补充
大部分文章来自:
http://www.socher.org/
http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial
包括从他们里面的论文里找到的related work
Word Embedding Learnig
SENNA原始论文【ACL'07】Fast Semantic Extraction Using a Novel Neural Network Architecture
Ronan Collobert and Jason Weston【ICML'08】A unified architecture for natural language processing: deep neural networks with multitask learning
Joseph Turian, et al.【ACL'10】Word representations:A simple and general method for semi-supervised learning
Antoine Bordes, et al. 【AAAI'11】Learning Structured Embeddings of Knowledge Bases
our model learns one embedding for each entity (i.e. one low dimensional vector) and one operator for each relation (i.e. a matrix).
Ronan Collobert, et al.【JMLR'12】Natural Language Processing (Almost) from Scratch
Eric H. Huang, et al.【ACL'12】Improving Word Representations via Global Context and Multiple Word Prototypes
T. Mikolov, et al.【HLT-NAACL'13】Linguistic regularities in continuous spaceword representations
Yoshua Bengio et al,【13】 Representation Learning: A Review and New Perspectives
待读列表:
Semi-supervised learning of compact document representations with deep networks
【UAI'13】Modeling Documents with a Deep Boltzmann Machine
Language Model
Y. Bengio, et al. Neural probabilistic language model
博士论文:Statistical Language Models based on Neural Networks 这人貌似在ICASSP上有个文章
T Mikolov Statistical Language Models Based on Neural Networks
Sentiment
【HLT'11】Learning word vectors for sentiment analysis
【EMNLP'11】Semi-supervised recursive autoencoders for predicting sentiment distributions
【NAACL'13】 Discourse Connectors for Latent Subjectivity in Sentiment Analysis
other NLP 以下内容见socher主页
Parsing with Compositional Vector Grammars
Better Word Representations with Recursive Neural Networks for Morphology
Semantic Compositionality through Recursive Matrix-Vector Spaces
Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection
Parsing Natural Scenes and Natural Language with Recursive Neural Networks
Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks
Semantic Compositionality through Recursive Matrix-Vector Spaces
Dynamic Pooling and Unfolding Recursive Autoencoders for Paraphrase Detection
Parsing Natural Scenes and Natural Language with Recursive Neural Networks
Learning Continuous Phrase Representations and Syntactic Parsing with Recursive Neural Networks
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing
Tutorials
Ronan Collobert and Jason Weston【NIPS'09】Deep Learning for Natural Language Processing
Richard Socher, et al.【NAACL'13】【ACL'12】Deep Learning for NLP
Yoshua Bengio【ICML'12】Representation Learning
Leon Bottou, Natural language processing and weak supervision
Yoshua Bengio最新AAAI 2013 tutorial:http://www.iro.umontreal.ca/~bengioy/talks/aaai2013-tutorial.pdf
Socher NAACL 2013:http://nlp.stanford.edu/courses/NAACL2013/
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