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Sparse Overcomplete Word Vector Representations
Manaal Faruqui
|
Yulia Tsvetkov
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Dani Yogatama
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Chris Dyer
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Noah A. Smith
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Paper Details:
Month: July
Year: 2015
Location: Beijing, China
Venue:
ACL |
IJCNLP |
Citations
URL
Neural-based Noise Filtering from Word Embeddings
Kim Anh Nguyen
|
Sabine Schulte im Walde
|
Ngoc Thang Vu
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Why does PairDiff work? - A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection
Huda Hakami
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Kohei Hayashi
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Danushka Bollegala
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A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution
Shaohua Li
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Jun Zhu
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Chunyan Miao
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Rationalizing Neural Predictions
Tao Lei
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Regina Barzilay
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Tommi Jaakkola
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Rotated Word Vector Representations and their Interpretability
Sungjoon Park
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JinYeong Bak
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Alice Oh
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A Factored Neural Network Model for Characterizing Online Discussions in Vector Space
Hao Cheng
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Hao Fang
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Mari Ostendorf
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The strange geometry of skip-gram with negative sampling
David Mimno
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Laure Thompson
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Sparse Bilingual Word Representations for Cross-lingual Lexical Entailment
Yogarshi Vyas
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Marine Carpuat
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Non-distributional Word Vector Representations
Manaal Faruqui
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Chris Dyer
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Compressing Neural Language Models by Sparse Word Representations
Yunchuan Chen
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Lili Mou
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Yan Xu
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Ge Li
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Zhi Jin
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Word Embeddings with Limited Memory
Shaoshi Ling
|
Yangqiu Song
|
Dan Roth
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An Interpretable Knowledge Transfer Model for Knowledge Base Completion
Qizhe Xie
|
Xuezhe Ma
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Zihang Dai
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Eduard Hovy
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Linear Algebraic Structure of Word Senses, with Applications to Polysemy
Sanjeev Arora
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Yuanzhi Li
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Yingyu Liang
|
Tengyu Ma
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Andrej Risteski
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Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov
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James Glass
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Functional Distributional Semantics
Guy Emerson
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Ann Copestake
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Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations
José Camacho-Collados
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Roberto Navigli
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Elucidating Conceptual Properties from Word Embeddings
Kyoung-Rok Jang
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Sung-Hyon Myaeng
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Firearms and Tigers are Dangerous, Kitchen Knives and Zebras are Not: Testing whether Word Embeddings Can Tell
Pia Sommerauer
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Antske Fokkens
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Interpretable Word Embedding Contextualization
Kyoung-Rok Jang
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Sung-Hyon Myaeng
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Sang-Bum Kim
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https://github.com/mfaruqui/
http://www-nlp.stanford.edu/projects/
https://code.google.com/p/word2vec
http://nlp.stanford.edu/
http://cs.cmu.edu/
http://qwone.com/
Field Of Study
Linguistic Trends
Lexical Semantics
Task
Tagging
Sentiment Analysis
Question Answering
Approach
Bayesian Model
Representation Learning
Language
Multilingual
English
Dataset
News
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