Difference between revisions of "Reading table"

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*Text segmentation based on semantic word embeddings[http://arxiv.org/abs/1503.05543]
 
*Text segmentation based on semantic word embeddings[http://arxiv.org/abs/1503.05543]
 
*semantic parsing via paraphrashings[http://www.cs.tau.ac.il/research/jonathan.berant/homepage_files/publications/ACL14.pdf]
 
*semantic parsing via paraphrashings[http://www.cs.tau.ac.il/research/jonathan.berant/homepage_files/publications/ACL14.pdf]
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|2015/07/22 ||Dong Wang||
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*From Word Embeddings To Document Distances [http://jmlr.org/proceedings/papers/v37/kusnerb15.pdf pdf]
 
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Revision as of 04:43, 22 July 2015

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
  • From Word Embeddings To Document Distances pdf