Deep Learning for NLP 文章列举

原文地址：http://www.xperseverance.net/blogs/2013/07/2124/?utm_source=rss&utm_medium=rss&utm_campaign=deep-learning-for-nlp-%25e6%2596%2587%25e7%25ab%25a0%25e5%2588%2597%25e4%25b8%25be

发表日期：2013 年 7 月 9 日

分类：  Academics   标签：  Deep Learning   作者： 恒.  101 views

慢慢补充

大部分文章来自 http://www.socher.org/ 包括从他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

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

 

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目测今年ACL best paper候选哦

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

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