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Information bottleneck (IB) is a method for extracting information from one random variable $X$ that is relevant for predicting another random variable $Y$.
Source coding with Side Information and a Converse for Degraded Broadcast Channels
Rudolf Ahlswede and János Körner · 1975
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A conditional entropy bound for a pair of discrete random variables
H. Witsenhausen and A. Wyner · 1975
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Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Nonlinear multiobjective optimization, volume 12 of international series in operations research and management science, 1999
Kaisa Miettinen · 1999
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The information bottleneck method
N. Tishby, F. Pereira, and W. Bialek · 1999
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Document clustering using word clusters via the information bottleneck method
Noam Slonim and Naftali Tishby · 2000
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Compression of side information
Jean Cardinal · 2003
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An Information Theoretic Tradeoff between Complexity and Accuracy
Ran Gilad-Bachrach, Amir Navot, and Naftali Tishby · 2003
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Estimating Mutual Information Via Kolmogorov Distance
Zhengmin Zhang · 2007
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Design of network coding functions in multihop relay networks
Georg Zeitler, Ralf Koetter, Gerhard Bauch, and Joerg Widmer · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning and generalization with the information bottleneck
Ohad Shamir, Sivan Sabato, and Naftali Tishby · 2010
Earlier work this paper cites.
Multiterminal source coding with an entropy-based distortion measure
Thomas A Courtade and Richard D Wesel · 2011
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Elements of information theory
Thomas M. Cover and Joy A. Thomas · 2012
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Cited alongside, same era.
Convex analysis
Ralph Tyrell Rockafellar · 2015
Cited alongside, same era.
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
Cited alongside, same era.
Deep learning and the information bottleneck principle
Naftali Tishby and Noga Zaslavsky · 2015
Cited alongside, same era.
Deep Variational Information Bottleneck
Alexander A. Alemi, Ian Fischer, Joshua V. Dillon, and Kevin Murphy · 2016
The Deterministic Information Bottleneck
Dj Strouse and David J. Schwab · 2017
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Understanding deep learning requires rethinking generalization
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, and Oriol Vinyals · 2017
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Information dropout: Learning optimal representations through noisy computation
Alessandro Achille and Stefano Soatto · 2018
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Uncertainty in the variational information bottleneck
Alexander A Alemi, Ian Fischer, and Joshua V Dillon · 2018
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Rana Ali Amjad and Bernhard C Geiger · 2018
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Cited alongside, same era.
Relevant sparse codes with variational information bottleneck
Matthew Chalk, Olivier Marre, and Gasper Tkacik · 2016
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
Cited alongside, same era.
Estimating mixture entropy with pairwise distances
Artemy Kolchinsky and Brendan D Tracey · 2017
Cited alongside, same era.
Nonlinear Information Bottleneck
Artemy Kolchinsky, Brendan D. Tracey, and David H. Wolpert · 2017
Cited alongside, same era.
Opening the black box of deep neural networks via information
Ravid Shwartz-Ziv and Naftali Tishby · 2017
Cited alongside, same era.
Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R Devon Hjelm, and Aaron Courville · 2018
Closest in time.
Compressing neural networks using the variational information bottleneck
Bin Dai, Chen Zhu, and David Wipf · 2018
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Entropy and mutual information in models of deep neural networks
Marylou Gabrié, Andre Manoel, Clément Luneau, Jean Barbier, Nicolas Macris, Florent Krzakala, and Lenka Zdeborová · 2018
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Estimating information flow in neural networks
Ziv Goldfeld, Ewout van den Berg, Kristjan Greenewald, Igor Melnyk, Nam Nguyen, Brian Kingsbury, and Yury Polyanskiy · 2018
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On the information bottleneck theory of deep learning
AM Saxe, Y Bansal, J Dapello, M Advani, A Kolchinsky, BD Tracey, and DD Cox · 2018
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The role of the information bottleneck in representation learning
Matias Vera, Pablo Piantanida, and Leonardo Rey Vega · 2018
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Efficient compression in color naming and its evolution
Noga Zaslavsky, Charles Kemp, Terry Regier, and Naftali Tishby · 2018
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