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This paper introduces a variational approximation framework using direct optimization of what is known as the {\it scale invariant Alpha-Beta divergence} (sAB divergence).
On information and sufficiency
Kullback, Solomon and Leibler, Richard A · 1951
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On information and sufficiency
Kullback, Solomon and Leibler, Richard A · 1951
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Rényi, Alfréd et al · 1961
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Rényi, Alfréd et al · 1961
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Efficiency versus robustness: the case for minimum hellinger distance and related methods
Lindsay, Bruce G · 1994
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Efficiency versus robustness: the case for minimum hellinger distance and related methods
Lindsay, Bruce G · 1994
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Robust and efficient estimation by minimising a density power divergence
Basu, Ayanendranath, Harris, Ian R, Hjort, Nils L, and Jones, MC · 1998
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Robust and efficient estimation by minimising a density power divergence
Basu, Ayanendranath, Harris, Ian R, Hjort, Nils L, and Jones, MC · 1998
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An introduction to variational methods for graphical models
Jordan, Michael I, Ghahramani, Zoubin, Jaakkola, Tommi S, and Saul, Lawrence K · 1999
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An introduction to variational methods for graphical models
Jordan, Michael I, Ghahramani, Zoubin, Jaakkola, Tommi S, and Saul, Lawrence K · 1999
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Monte carlo optimization
Robert, Christian P and Casella, George · 2004
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Monte carlo optimization
Robert, Christian P and Casella, George · 2004
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Minka, Tom · 2005
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Robust parameter estimation with a small bias against heavy contamination
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Robust parameter estimation with a small bias against heavy contamination
Fujisawa, Hironori and Eguchi, Shinto · 2008
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On over-fitting in model selection and subsequent selection bias in performance evaluation
Cawley, Gavin C and Talbot, Nicola LC · 2010
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Families of alpha-beta-and gamma-divergences: Flexible and robust measures of similarities
Cichocki, Andrzej and Amari, Shun-ichi · 2010
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On over-fitting in model selection and subsequent selection bias in performance evaluation
Cawley, Gavin C and Talbot, Nicola LC · 2010
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Families of alpha-beta-and gamma-divergences: Flexible and robust measures of similarities
Cichocki, Andrzej and Amari, Shun-ichi · 2010
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Generalized alpha-beta divergences and their application to robust nonnegative matrix factorization
Cichocki, Andrzej, Cruces, Sergio, and Amari, Shun-ichi · 2011
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Algorithms for nonnegative matrix factorization with the β \beta -divergence
Févotte, Cédric and Idier, Jérôme · 2011
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Two problems with variational expectation maximisation for time-series models
Turner, Richard E and Sahani, Maneesh · 2011
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Generalized alpha-beta divergences and their application to robust nonnegative matrix factorization
Cichocki, Andrzej, Cruces, Sergio, and Amari, Shun-ichi · 2011
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Algorithms for nonnegative matrix factorization with the β \beta -divergence
Févotte, Cédric and Idier, Jérôme · 2011
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Two problems with variational expectation maximisation for time-series models
Adam: A method for stochastic optimization
Kingma, Diederik P and Ba, Jimmy · 2014
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On the chi square and higher-order chi distances for approximating f-divergences
Nielsen, Frank and Nock, Richard · 2014
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Rényi divergence and kullback-leibler divergence
Van Erven, Tim and Harremos, Peter · 2014
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Log-euclidean metric learning on symmetric positive definite manifold with application to image set classification
Huang, Zhiwu, Wang, Ruiping, Shan, Shiguang, Li, Xianqiu, and Chen, Xilin · 2015
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Log-euclidean metric learning on symmetric positive definite manifold with application to image set classification
Huang, Zhiwu, Wang, Ruiping, Shan, Shiguang, Li, Xianqiu, and Chen, Xilin · 2015
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Turner, Richard E and Sahani, Maneesh · 2011
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Differential-geometrical methods in statistics , volume 28
Amari, Shun-ichi · 2012
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Machine learning: a probabilistic perspective
Murphy, Kevin P · 2012
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Bayesian learning for neural networks , volume 118
Neal, Radford M · 2012
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Differential-geometrical methods in statistics , volume 28
Amari, Shun-ichi · 2012
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Machine learning: a probabilistic perspective
Murphy, Kevin P · 2012
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Bayesian learning for neural networks , volume 118
Neal, Radford M · 2012
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Depeweg, Stefan, Hernández-Lobato, José Miguel, Doshi-Velez, Finale, and Udluft, Steffen · 2016
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Robust bayes estimation using the density power divergence
Ghosh, Abhik and Basu, Ayanendranath · 2016
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Black-box α \alpha -divergence minimization
Hernández-Lobato, José Miguel, Li, Yingzhen, Rowland, Mark, Hernández-Lobato, Daniel, Bui, Thang D, and Turner, Richard E · 2016
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Rényi divergence variational inference
Li, Yingzhen and Turner, Richard E · 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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Learning and policy search in stochastic dynamical systems with bayesian neural networks
Depeweg, Stefan, Hernández-Lobato, José Miguel, Doshi-Velez, Finale, and Udluft, Steffen · 2016
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Robust bayes estimation using the density power divergence
Ghosh, Abhik and Basu, Ayanendranath · 2016
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Black-box α \alpha -divergence minimization
Hernández-Lobato, José Miguel, Li, Yingzhen, Rowland, Mark, Hernández-Lobato, Daniel, Bui, Thang D, and Turner, Richard E · 2016
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Rényi divergence variational inference
Li, Yingzhen and Turner, Richard E · 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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Variational inference based on robust divergences
Futami, Futoshi, Sato, Issei, and Sugiyama, Masashi · 2017
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A generalized divergence for statistical inference
Ghosh, Abhik, Harris, Ian R, Maji, Avijit, Basu, Ayanendranath, Pardo, Leandro, et al · 2017
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Variational inference based on robust divergences
Futami, Futoshi, Sato, Issei, and Sugiyama, Masashi · 2017
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A generalized divergence for statistical inference
Ghosh, Abhik, Harris, Ian R, Maji, Avijit, Basu, Ayanendranath, Pardo, Leandro, et al · 2017
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