Geoffrey Hinton

Lookahead Optimizer: k steps forward, 1 step back

Michael R. Zhang, James Lucas, Geoffrey Hinton, Jimmy Ba

Comments Accepted to Neural Information Processing Systems 2019. Code available at: https://github.com/michaelrzhang/lookahead

Stacked Capsule Autoencoders

Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton

Comments NeurIPS 2019; 14 pages, 7 figures, 4 tables, code is available at https://github.com/google-research/google-research/tree/master/stacked_capsule_autoencoders

Learning Sparse Networks Using Targeted Dropout

Aidan N. Gomez, Ivan Zhang, Siddhartha Rao Kamalakara, Divyam Madaan, Kevin Swersky, Yarin Gal, Geoffrey E. Hinton

Similarity of Neural Network Representations Revisited

Simon Kornblith, Mohammad Norouzi, Honglak Lee, Geoffrey Hinton

Comments ICML 2019

Cerberus: A Multi-headed Derenderer

Boyang Deng, Simon Kornblith, Geoffrey Hinton

Analyzing and Improving Representations with the Soft Nearest Neighbor Loss

Nicholas Frosst, Nicolas Papernot, Geoffrey Hinton

Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures

Sergey Bartunov, Adam Santoro, Blake A. Richards, Luke Marris, Geoffrey E. Hinton, Timothy Lillicrap

Comments NIPS 2018. Version 2 contains more experimental data including best hyperparameters found

DARCCC: Detecting Adversaries by Reconstruction from Class Conditional Capsules

Nicholas Frosst, Sara Sabour, Geoffrey Hinton

Comments To be presented at NIPS 2018 Workshop on Security in Machine Learning

Who Said What: Modeling Individual Labelers Improves Classification

Melody Y. Guan, Varun Gulshan, Andrew M. Dai, Geoffrey E. Hinton

Comments AAAI 2018

Distilling a Neural Network Into a Soft Decision Tree

Nicholas Frosst, Geoffrey Hinton

Comments presented at the CEX workshop at AI*IA 2017 conference

Dynamic Routing Between Capsules

Sara Sabour, Nicholas Frosst, Geoffrey E Hinton

Regularizing Neural Networks by Penalizing Confident Output Distributions

Gabriel Pereyra, George Tucker, Jan Chorowski, Łukasz Kaiser, Geoffrey Hinton

Comments Submitted to ICLR 2017

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean

Using Fast Weights to Attend to the Recent Past

Jimmy Ba, Geoffrey Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu

Comments Added [Schmidhuber 1993] citation to the last paragraph of the introduction. Fixed typo appendix A.1 uniform initialization to 1/\sqrt{H}

Attend, Infer, Repeat: Fast Scene Understanding with Generative Models

S. M. Ali Eslami, Nicolas Heess, Theophane Weber, Yuval Tassa, David Szepesvari, Koray Kavukcuoglu, Geoffrey E. Hinton

Layer Normalization

Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton

Grammar as a Foreign Language

Oriol Vinyals, Lukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey Hinton

A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

Quoc V. Le, Navdeep Jaitly, Geoffrey E. Hinton

Distilling the Knowledge in a Neural Network

Geoffrey Hinton, Oriol Vinyals, Jeff Dean

Comments NIPS 2014 Deep Learning Workshop

Modeling Documents with Deep Boltzmann Machines

Nitish Srivastava, Ruslan R Salakhutdinov, Geoffrey E. Hinton

Comments Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013)

Speech Recognition with Deep Recurrent Neural Networks

Alex Graves, Abdel-rahman Mohamed, Geoffrey Hinton

Comments To appear in ICASSP 2013

Discovering Multiple Constraints that are Frequently Approximately Satisfied

Geoffrey E. Hinton, Yee Whye Teh

Comments Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001)

Efficient Parametric Projection Pursuit Density Estimation

Max Welling, Richard S. Zemel, Geoffrey E. Hinton

Comments Appears in Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)

Improving neural networks by preventing co-adaptation of feature detectors

Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, Ruslan R. Salakhutdinov

Deep Lambertian Networks

Yichuan Tang, Ruslan Salakhutdinov, Geoffrey Hinton

Comments Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)

Deep Mixtures of Factor Analysers

Yichuan Tang, Ruslan Salakhutdinov, Geoffrey Hinton

Comments ICML2012

Products of Hidden Markov Models: It Takes N>1 to Tango

Graham W Taylor, Geoffrey E. Hinton

Comments Appears in Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence (UAI2009)

Conditional Restricted Boltzmann Machines for Structured Output Prediction

Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton