Ilya Sutskever

Learning to Generate Reviews and Discovering Sentiment

Alec Radford, Rafal Jozefowicz, Ilya Sutskever

Variational Lossy Autoencoder

Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel

Comments Added CIFAR10 experiments; ICLR 2017

Improving Variational Inference with Inverse Autoregressive Flow

Diederik P. Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, Max Welling

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

Yan Duan, John Schulman, Xi Chen, Peter L. Bartlett, Ilya Sutskever, Pieter Abbeel

Comments 14 pages. Under review as a conference paper at ICLR 2017

Extensions and Limitations of the Neural GPU

Eric Price, Wojciech Zaremba, Ilya Sutskever

A Neural Transducer

Navdeep Jaitly, David Sussillo, Quoc V. Le, Oriol Vinyals, Ilya Sutskever, Samy Bengio

Neural Programmer: Inducing Latent Programs with Gradient Descent

Arvind Neelakantan, Quoc V. Le, Ilya Sutskever

Comments Accepted as a conference paper at ICLR 2015

Learning Online Alignments with Continuous Rewards Policy Gradient

Yuping Luo, Chung-Cheng Chiu, Navdeep Jaitly, Ilya Sutskever

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, Pieter Abbeel

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

Comments Version 2 updates only the metadata, to correct the formatting of Martín Abadi's name

Neural GPUs Learn Algorithms

Łukasz Kaiser, Ilya Sutskever

Multi-task Sequence to Sequence Learning

Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser

Comments 10 pages, 4 figures, ICLR 2016 camera-ready, added parsing SOTA results

MuProp: Unbiased Backpropagation for Stochastic Neural Networks

Shixiang Gu, Sergey Levine, Ilya Sutskever, Andriy Mnih

Comments Published as a conference paper at ICLR 2016

Neural Random-Access Machines

Karol Kurach, Marcin Andrychowicz, Ilya Sutskever

Comments ICLR submission, 17 pages, 9 figures, 6 tables (with bibliography and appendix)

Reinforcement Learning Neural Turing Machines - Revised

Wojciech Zaremba, Ilya Sutskever

Towards Principled Unsupervised Learning

Ilya Sutskever, Rafal Jozefowicz, Karol Gregor, Danilo Rezende, Tim Lillicrap, Oriol Vinyals

Adding Gradient Noise Improves Learning for Very Deep Networks

Arvind Neelakantan, Luke Vilnis, Quoc V. Le, Ilya Sutskever, Lukasz Kaiser, Karol Kurach, James Martens

Learning to Execute

Wojciech Zaremba, Ilya Sutskever

Grammar as a Foreign Language

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

Addressing the Rare Word Problem in Neural Machine Translation

Minh-Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba

Comments ACL 2015 camera-ready version

Move Evaluation in Go Using Deep Convolutional Neural Networks

Chris J. Maddison, Aja Huang, Ilya Sutskever, David Silver

Comments Minor edits and included captures in Figure 2

Recurrent Neural Network Regularization

Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals

Sequence to Sequence Learning with Neural Networks

Ilya Sutskever, Oriol Vinyals, Quoc V. Le

Comments 9 pages

Learning Factored Representations in a Deep Mixture of Experts

David Eigen, Marc'Aurelio Ranzato, Ilya Sutskever

Intriguing properties of neural networks

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, Rob Fergus

Distributed Representations of Words and Phrases and their Compositionality

Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean

Exploiting Similarities among Languages for Machine Translation

Tomas Mikolov, Quoc V. Le, Ilya Sutskever

Estimating the Hessian by Back-propagating Curvature

James Martens, Ilya Sutskever, Kevin Swersky

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

Improving neural networks by preventing co-adaptation of feature detectors

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