“Reading table”版本间的差异

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|2015/08/07 ||Chao Xing||  
 
|2015/08/07 ||Chao Xing||  
 
* Neural Word Embedding as Implicit Matrix Factorization [[http://papers.nips.cc/paper/5477-neural-word-embedding-as-implicit-matrix-factorization.pdf pdf]]
 
* Neural Word Embedding as Implicit Matrix Factorization [[http://papers.nips.cc/paper/5477-neural-word-embedding-as-implicit-matrix-factorization.pdf pdf]]
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* Matrix factorization techniques for recommender systems [[https://datajobs.com/data-science-repo/Recommender-Systems-[Netflix].pdf]]
 
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2015年8月11日 (二) 01:51的版本

Date Speaker Materials
2014/10/22 Zhang Dong Xu Why RNN? PPT paper 1,paper 2
2014/12/8 Liu Rong Yu Zhao, Zhiyuan Liu, Maosong Sun. Phrase Type Sensitive Tensor Indexing Model for Semantic Composition. AAAI'15. pdf
Yang Liu, Zhiyuan Liu, Tat-Seng Chua, Maosong Sun. Topical Word Embeddings. AAAI'15. pdfcode
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, Xuan Zhu. Learning Entity and Relation Embeddings for Knowledge Graph Completion. AAAI'15. pdfcode
2015/07/10 Liu Rong
  • Context-Dependent Translation Selection Using Convolutional Neural Network [1]
  • Syntax-based Deep Matching of Short Texts [2]
  • Convolutional Neural Network Architectures for Matching Natural Language Sentences[3]
  • LSTM: A Search Space Odyssey [4]
  • A Deep Embedding Model for Co-occurrence Learning [5]
  • Text segmentation based on semantic word embeddings[6]
  • semantic parsing via paraphrashings[7]
2015/07/22 Dong Wang
2015/07/29 Xiaoxi Wang
  • some related to sequence to sequence[ pdf]
2015/08/05 Dongxu Zhang
  • some related to sequence to sequence[ pdf]
2015/08/07 Chao Xing
  • Neural Word Embedding as Implicit Matrix Factorization [pdf]
  • Matrix factorization techniques for recommender systems [[Netflix.pdf]]