Layer-wise Learning of Stochastic Neural Networks with Information Bottleneck

4 December 2017

Thanh T. Nguyen

Papers citing "Layer-wise Learning of Stochastic Neural Networks with Information Bottleneck"

36 / 36 papers shown

Title
Bayesian Optimization with Unknown Search Space Huong Ha Santu Rana Sunil R. Gupta Thanh Nguyen Hung The Tran Svetha Venkatesh 42 22 0 29 Oct 2019
On Mutual Information Maximization for Representation Learning Michael Tschannen Josip Djolonga Paul Kishan Rubenstein Sylvain Gelly Mario Lucic SSL 174 495 0 31 Jul 2019
Data-Efficient Mutual Information Neural Estimator Xiaoyu Lin Indranil Sur Samuel A. Nastase Ajay Divakaran Uri Hasson Mohamed R. Amer DRL 69 21 0 08 May 2019
FAVAE: Sequence Disentanglement using Information Bottleneck Principle Masanori Yamada Heecheol Kim Kosuke Miyoshi Hiroshi Yamakawa CML DRL CoGe 24 4 0 22 Feb 2019
InfoBot: Transfer and Exploration via the Information Bottleneck Anirudh Goyal Riashat Islam Daniel Strouse Zafarali Ahmed M. Botvinick Hugo Larochelle Yoshua Bengio Sergey Levine OffRL 78 166 0 30 Jan 2019
Compressing Neural Networks using the Variational Information Bottleneck Bin Dai Chen Zhu David Wipf MLT 51 181 0 28 Feb 2018
Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle Rana Ali Amjad Bernhard C. Geiger 71 196 0 27 Feb 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 86 642 0 14 Feb 2018
MINE: Mutual Information Neural Estimation Mohamed Ishmael Belghazi A. Baratin Sai Rajeswar Sherjil Ozair Yoshua Bengio Aaron Courville R. Devon Hjelm DRL 191 1,279 0 12 Jan 2018
The information bottleneck and geometric clustering D. Strouse D. Schwab 35 35 0 27 Dec 2017
A Survey of Model Compression and Acceleration for Deep Neural Networks Yu Cheng Duo Wang Pan Zhou Zhang Tao 72 1,095 0 23 Oct 2017
Emergence of Invariance and Disentanglement in Deep Representations Alessandro Achille Stefano Soatto OOD DRL 88 476 0 05 Jun 2017
Stochastic Neural Networks for Hierarchical Reinforcement Learning Carlos Florensa Yan Duan Pieter Abbeel BDL 87 361 0 10 Apr 2017
Opening the Black Box of Deep Neural Networks via Information Ravid Shwartz-Ziv Naftali Tishby AI4CE 100 1,409 0 02 Mar 2017
Deep Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon Kevin Patrick Murphy 121 1,721 0 01 Dec 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 264 8,552 0 16 Aug 2016
Relevant sparse codes with variational information bottleneck M. Chalk O. Marre G. Tkačik 99 87 0 24 May 2016
Theano: A Python framework for fast computation of mathematical expressions The Theano Development Team Rami Al-Rfou Guillaume Alain Amjad Almahairi Christof Angermüller ... Kelvin Xu Lijun Xue Li Yao Saizheng Zhang Ying Zhang 198 2,341 0 09 May 2016
The deterministic information bottleneck D. Strouse D. Schwab 55 135 0 01 Apr 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Predicting distributions with Linearizing Belief Networks Yann N. Dauphin David Grangier 59 18 0 17 Nov 2015
StochasticNet: Forming Deep Neural Networks via Stochastic Connectivity M. Shafiee P. Siva A. Wong 50 29 0 22 Aug 2015
Deep Learning and the Information Bottleneck Principle Naftali Tishby Noga Zaslavsky DRL 207 1,584 0 09 Mar 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,305 0 11 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 162 3,271 0 05 Dec 2014
Going Deeper with Convolutions Christian Szegedy Wei Liu Yangqing Jia P. Sermanet Scott E. Reed Dragomir Anguelov D. Erhan Vincent Vanhoucke Andrew Rabinovich 465 43,658 0 17 Sep 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 558 27,311 0 01 Sep 2014
Techniques for Learning Binary Stochastic Feedforward Neural Networks T. Raiko Mathias Berglund Guillaume Alain Laurent Dinh BDL 103 126 0 11 Jun 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 1.0K 23,354 0 03 Jun 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,927 1 21 Dec 2013
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,933 0 20 Dec 2013
Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation Yoshua Bengio Nicholas Léonard Aaron Courville 381 3,135 0 15 Aug 2013
Multivariate Information Bottleneck N. Friedman Ori Mosenzon Noam Slonim Naftali Tishby 77 221 0 10 Jan 2013
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 152 6,625 0 22 Dec 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 261 12,439 0 24 Jun 2012