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|1/17||Mikolov, Tomas, Wen-tau Yih, and Geoffrey Zweig. "Linguistic Regularities in Continuous Space Word Representations." In NAACL 2013|
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. "Efficient
Estimation of Word Representations in Vector Space."
In ICLR, 2013.
See also this paper and this note that provides an explanation.
|1/31||Pennington, Jeffrey, Richard Socher, and Christopher D. Manning. "Glove: Global Vectors for Word Representation." In EMNLP 2014.|
|2/7||Levy, Omer, Yoav Goldberg, and Israel Ramat-Gan. "Linguistic Regularities in Sparse and Explicit Word Representations." In CoNLL 2014.|
|2/14||Baroni, Marco, Georgiana Dinu, and Germán Kruszewski. " Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors" In ACL 2014.|
|2/21||Arora, Sanjeev, et al. "A latent variable model approach to PMI-based word embeddings" Transactions of the Association for Computational Linguistics 4 (2016): 385-399.|
|2/28||Mnih, Andriy, and Koray Kavukcuoglu. "Learning word embeddings efficiently with noise-contrastive estimation." In NIPS 2013.|
|3/7||Levy, Omer, and Yoav Goldberg. "Neural word embedding as implicit matrix factorization." In NIPS 2014.|
|3/14||Spring break. No meeting|
|3/21||Rocktäschel, Tim, Sameer Singh, and Sebastian Riedel. "Injecting logical background knowledge into embeddings for relation extraction." In NAACL 2015.|
|3/28||Blacoe, William, and Mirella Lapata. "A comparison of vector-based representations for semantic composition." In EMNLP 2012.|
|4/4||Li, Jiwei and Dan Jurafsky. 2015. "Do multi-sense embeddings improve natural language understanding?" In EMNLP 2015.|
|4/11||Suster, Simon, Ivan Titov and Gertjan van Noord. NAACL, 2016. "Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders", In NAACL 2016.|
|4/18||Roth, Michael and Mirella Lapata. "Neural Semantic Role Labeling with Dependency Path Embeddings". In ACL 2016.|