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Word embeddings are a powerful approach for unsupervised analysis of language.
On the theory of the brownian motion
Uhlenbeck, George E and Ornstein, Leonard S · 1930
Earlier work this paper cites.
A stochastic approximation method
Robbins, Herbert and Monro, Sutton · 1951
Earlier work this paper cites.
Distributional structure
Harris, Zellig S · 1954
Earlier work this paper cites.
Learning representations by back-propagating errors
Rumelhart, David E, Hintont, Geoffrey E, and Williams, Ronald J · 1986
Earlier work this paper cites.
Language change: progress or decay?
Aitchison, Jean · 2001
Earlier work this paper cites.
Conditionally specified distributions: an introduction (with comments and a rejoinder by the authors)
Arnold, Barry C, Castillo, Enrique, Sarabia, Jose Maria, et al · 2001
Earlier work this paper cites.
A neural probabilistic language model
Bengio, Yoshua, Ducharme, Réjean, Vincent, Pascal, and Jauvin, Christian · 2003
Earlier work this paper cites.
Latent dirichlet allocation
Blei, David M, Ng, Andrew Y, and Jordan, Michael I · 2003
Earlier work this paper cites.
Machine learning and pattern recognition
Bishop, Christopher M · 2006
Earlier work this paper cites.
Dynamic topic models
Blei, David M and Lafferty, John D · 2006
Earlier work this paper cites.
Topics over time: a non-markov continuous-time model of topical trends
Wang, Xuerui and McCallum, Andrew · 2006
Earlier work this paper cites.
Innateness and culture in the evolution of language
Kirby, Simon, Dowman, Mike, and Griffiths, Thomas L · 2007
Earlier work this paper cites.
Collaborative filtering for implicit feedback datasets
Hu, Yifan, Koren, Yehuda, and Volinsky, Chris · 2008
Earlier work this paper cites.
Continuous time dynamic topic models
Wang, C., Blei, D., and Heckerman, D · 2008
Earlier work this paper cites.
A language-based approach to measuring scholarly impact
Gerrish, S. and Blei, D · 2010
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Noise-contrastive estimation: A new estimation principle for unnormalized statistical models
Gutmann, Michael and Hyvärinen, Aapo · 2010
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Adaptive subgradient methods for online learning and stochastic optimization
Duchi, John, Hazan, Elad, and Singer, Yoram · 2011
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Tracing semantic change with latent semantic analysis
Sagi, Eyal, Kaufmann, Stefan, and Clark, Brady · 2011
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Understanding semantic change of words over centuries
Wijaya, Derry Tanti and Yeniterzi, Reyyan · 2011
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Word epoch disambiguation: Finding how words change over time
Mihalcea, Rada and Nastase, Vivi · 2012
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Rand-walk: A latent variable model approach to word embeddings
Arora, Sanjeev, Li, Yuanzhi, Liang, Yingyu, Ma, Tengyu, and Risteski, Andrej · 2015
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Statistically significant detection of linguistic change
Kulkarni, Vivek, Al-Rfou, Rami, Perozzi, Bryan, and Skiena, Steven · 2015
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An automatic approach to identify word sense changes in text media across timescales
Mitra, Sunny, Mitra, Ritwik, Maity, Suman Kalyan, Riedl, Martin, Biemann, Chris, Goyal, Pawan, and Mukherjee, Animesh · 2015
Later among the works it cites.
TensorFlow: Large-scale machine learning on heterogeneous systems, 2015
Team, Tensorflow · 2015
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Dynamic word embeddings via skip-gram filtering
Bamler, Robert and Mandt, Stephan · 2016
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Machine learning: a probabilistic perspective
Murphy, Kevin P · 2012
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Learning word embeddings efficiently with noise-contrastive estimation
Mnih, Andriy and Kavukcuoglu, Koray · 2013
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Analysing word meaning over time by exploiting temporal random indexing
Basile, Pierpaolo, Caputo, Annalina, and Semeraro, Giovanni · 2014
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Temporal analysis of language through neural language models
Kim, Yoon, Chiu, Yi-I, Hanaki, Kentaro, Hegde, Darshan, and Petrov, Slav · 2014
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Neural word embedding as implicit matrix factorization
Levy, Omer and Goldberg, Yoav · 2014
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That’s sick dude!: Automatic identification of word sense change across different timescales
Mitra, Sunny, Mitra, Ritwik, Riedl, Martin, Biemann, Chris, Mukherjee, Animesh, and Goyal, Pawan · 2014
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A bayesian model of diachronic meaning change
Frermann, Lea and Lapata, Mirella · 2016
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Diachronic word embeddings reveal statistical laws of semantic change
Hamilton, William L, Leskovec, Jure, and Jurafsky, Dan · 2016
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Modeling user exposure in recommendation
Liang, Dawen, Charlin, Laurent, McInerney, James, and Blei, David M · 2016
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Exponential family embeddings
Rudolph, Maja, Ruiz, Francisco, Mandt, Stephan, and Blei, David · 2016
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Semantic change computation: A successive approach
Tang, Xuri, Qu, Weiguang, and Chen, Xiaohe · 2016
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Edward: A library for probabilistic modeling, inference, and criticism
Tran, Dustin, Kucukelbir, Alp, Dieng, Adji B., Rudolph, Maja, Liang, Dawen, and Blei, David M · 2016
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The past is not a foreign country: Detecting semantically similar terms across time
Zhang, Yating, Jatowt, Adam, Bhowmick, Sourav S, and Tanaka, Katsumi · 2016
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Discovery of evolving semantics through dynamic word embedding learning
Yao, Zijun, Sun, Yifan, Ding, Weicong, Rao, Nikhil, and Xiong, Hui · 2017
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