Ilya Sutskever

发表

On the Convergence Properties of Contrastive Divergence

Ilya Sutskever, Tijmen Tieleman, Ilya Sutskever, 2010, AISTATS.

Generative Pretraining From Pixels

Mark Chen, Ilya Sutskever, Alec Radford, 2020, ICML.

Adding Gradient Noise Improves Learning for Very Deep Networks pdf

Quoc V. Le, Lukasz Kaiser, Ilya Sutskever, 2015, ArXiv.

Jukebox: A Generative Model for Music pdf

Ilya Sutskever, Alec Radford, Heewoo Jun, 2020, ArXiv.

Evolution Strategies as a Scalable Alternative to Reinforcement Learning pdf

Xi Chen, Tim Salimans, Ilya Sutskever, 2017, ArXiv.

Learning Multilevel Distributed Representations for High-Dimensional Sequences

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2007, AISTATS.

Using matrices to model symbolic relationship

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2008, NIPS.

Intriguing properties of neural networks pdf

Joan Bruna, Dumitru Erhan, Wojciech Zaremba, 2013, ICLR.

Improving neural networks by preventing co-adaptation of feature detectors pdf

Nitish Srivastava, Geoffrey E. Hinton, Ruslan Salakhutdinov, 2012, ArXiv.

Towards Principled Unsupervised Learning pdf

Oriol Vinyals, Karol Gregor, Ilya Sutskever, 2015, ArXiv.

Reinforcement Learning Neural Turing Machines - Revised

Wojciech Zaremba, Ilya Sutskever, Ilya Sutskever, 2015 .

Conditional Augmentation for Generative Modeling

Mark Chen, Ilya Sutskever, Alec Radford, 2020, ICML 2020.

Recurrent Neural Network Regularization pdf

Wojciech Zaremba, Oriol Vinyals, Ilya Sutskever, 2014, ArXiv.

On the importance of initialization and momentum in deep learning

Geoffrey E. Hinton, Ilya Sutskever, George E. Dahl, 2013, ICML.

Modelling Relational Data using Bayesian Clustered Tensor Factorization

Joshua B. Tenenbaum, Ruslan Salakhutdinov, Ilya Sutskever, 2009, NIPS.

Continuous Deep Q-Learning with Model-based Acceleration pdf

Sergey Levine, Ilya Sutskever, Shixiang Gu, 2016, ICML.

Multi-task Sequence to Sequence Learning pdf

Quoc V. Le, Lukasz Kaiser, Oriol Vinyals, 2015, ICLR.

Temporal-Kernel Recurrent Neural Networks

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2010, Neural Networks.

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

Peter L. Bartlett, Pieter Abbeel, Xi Chen, 2016, ArXiv.

Learning to Generate Reviews and Discovering Sentiment pdf

Ilya Sutskever, Alec Radford, Rafal Józefowicz, 2017, ArXiv.

Reinforcement Learning Neural Turing Machines pdf

Wojciech Zaremba, Ilya Sutskever, Ilya Sutskever, 2015, ArXiv.

Dota 2 with Large Scale Deep Reinforcement Learning pdf

Jakub W. Pachocki, Jie Tang, Tim Salimans, 2019, ArXiv.

Deep Neural Networks

Michael Guerzhoy, Ilya Sutskever, Ilya Sutskever, 2013 .

Generative Models for Alignment and Data Efficiency in Language

Dustin Tran, Ilya Sutskever, Yura Burda, 2018 .

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments pdf

Pieter Abbeel, Igor Mordatch, Ilya Sutskever, 2017, ICLR.

A Neural Transducer

Quoc V. Le, Navdeep Jaitly, Ilya Sutskever, 2015, 1511.04868.

Distribution Augmentation for Generative Modeling

Mark Chen, Ilya Sutskever, Alec Radford, 2020, ICML.

Neural Programmer: Inducing Latent Programs with Gradient Descent pdf

Quoc V. Le, Ilya Sutskever, Arvind Neelakantan, 2015, ICLR.

Quoc V. Le, Tomas Mikolov, Ilya Sutskever, 2013, ArXiv.

Parallelizable Sampling of Markov Random Fields

Ilya Sutskever, James Martens, 2010, AISTATS.

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey E. Hinton, Ruslan Salakhutdinov, 2014, J. Mach. Learn. Res..

The Importance of Sampling inMeta-Reinforcement Learning

Pieter Abbeel, Peter Chen, Ilya Sutskever, 2018, NeurIPS.

Extensions and Limitations of the Neural GPU pdf

Wojciech Zaremba, Ilya Sutskever, Eric Price, 2016, ArXiv.

Grammar as a Foreign Language

Geoffrey E. Hinton, Lukasz Kaiser, Oriol Vinyals, 2014, NIPS.

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems pdf

Martín Abadi, Martin Wattenberg, Michael Isard, 2016, ArXiv.

Generating Long Sequences with Sparse Transformers pdf

Ilya Sutskever, Alec Radford, Scott Gray, 2019, ArXiv.

An Online Sequence-to-Sequence Model Using Partial Conditioning

Samy Bengio, Quoc V. Le, Navdeep Jaitly, 2015, NIPS.

Move Evaluation in Go Using Deep Convolutional Neural Networks pdf

David Silver, Ilya Sutskever, Chris J. Maddison, 2014, ICLR.

Generating Text with Recurrent Neural Networks

Geoffrey E. Hinton, Ilya Sutskever, James Martens, 2011, ICML.

MuProp: Unbiased Backpropagation for Stochastic Neural Networks pdf

Sergey Levine, Ilya Sutskever, Andriy Mnih, 2015, ICLR.

Improving Variational Autoencoders with Inverse Autoregressive Flow

Max Welling, Tim Salimans, Ilya Sutskever, 2016, NIPS.

Learning Recurrent Neural Networks with Hessian-Free Optimization

Ilya Sutskever, James Martens, Ilya Sutskever, 2011, ICML.

Estimating the Hessian by Back-propagating Curvature

Ilya Sutskever, Kevin Swersky, James Martens, 2012, ICML.

ImageNet classification with deep convolutional neural networks

Geoffrey E. Hinton, Ilya Sutskever, Alex Krizhevsky, 2012, Commun. ACM.

Language Models are Few-Shot Learners pdf

Mark Chen, Ilya Sutskever, Alec Radford, 2020, NeurIPS.

A simpler unified analysis of budget perceptrons

Ilya Sutskever, Ilya Sutskever, 2009, ICML '09.

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

Pieter Abbeel, Xi Chen, Ilya Sutskever, 2016, NIPS.

Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning

Richard S. Zemel, Daniel Tarlow, Ilya Sutskever, 2013, ICML.

Emergent Complexity via Multi-Agent Competition pdf

Jakub W. Pachocki, Igor Mordatch, Ilya Sutskever, 2017, ICLR.

Learning Factored Representations in a Deep Mixture of Experts pdf

Marc'Aurelio Ranzato, Ilya Sutskever, David Eigen, 2013, ICLR.

An Empirical Exploration of Recurrent Network Architectures

Wojciech Zaremba, Ilya Sutskever, Rafal Józefowicz, 2015, ICML.

Neural GPUs Learn Algorithms

Lukasz Kaiser, Ilya Sutskever, Lukasz Kaiser, 2015, ICLR.

Neural Random Access Machines

Marcin Andrychowicz, Ilya Sutskever, Karol Kurach, 2015, ERCIM News.

Geoffrey E. Hinton, Ilya Sutskever, Andriy Mnih, 2007, AISTATS.

Variational Lossy Autoencoder pdf

Pieter Abbeel, Xi Chen, Tim Salimans, 2016, ICLR.

Third-Person Imitation Learning pdf

Pieter Abbeel, Ilya Sutskever, Bradly C. Stadie, 2017, ICLR.

Generative Language Modeling for Automated Theorem Proving pdf

Ilya Sutskever, Stanislas Polu, Ilya Sutskever, 2020, ArXiv.

FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models pdf

David Duvenaud, Ilya Sutskever, Ricky T. Q. Chen, 2018, ICLR.

Deep double descent: where bigger models and more data hurt pdf

Boaz Barak, Ilya Sutskever, Gal Kaplun, 2019, ICLR.

One-Shot Imitation Learning

Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel, 2017, NIPS.

Distributed Representations of Words and Phrases and their Compositionality pdf

Jeffrey Dean, Tomas Mikolov, Gregory S. Corrado, 2013, NIPS.

Sequence to Sequence Learning with Neural Networks

Quoc V. Le, Oriol Vinyals, Ilya Sutskever, 2014, NIPS.

Training Deep and Recurrent Networks with Hessian-Free Optimization

Ilya Sutskever, James Martens, Ilya Sutskever, 2012, Neural Networks: Tricks of the Trade.

Learning online alignments with continuous rewards policy gradient

Navdeep Jaitly, Ilya Sutskever, Chung-Cheng Chiu, 2016, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Deep, Narrow Sigmoid Belief Networks Are Universal Approximators

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2008, Neural Computation.

GamePad: A Learning Environment for Theorem Proving pdf

Dawn Xiaodong Song, Daniel Huang, Ilya Sutskever, 2018, ICLR.

Training Recurrent Neural Networks

Geoffrey E. Hinton, Ilya Sutskever, Ilya Sutskever, 2013 .

Addressing the Rare Word Problem in Neural Machine Translation

Quoc V. Le, Wojciech Zaremba, Oriol Vinyals, 2014, ACL.

Some Considerations on Learning to Explore via Meta-Reinforcement Learning pdf

Pieter Abbeel, Xi Chen, Ilya Sutskever, 2018, ICLR 2018.

Cardinality Restricted Boltzmann Machines

Ryan P. Adams, Ruslan Salakhutdinov, Richard S. Zemel, 2012, NIPS.

The Recurrent Temporal Restricted Boltzmann Machine

Geoffrey E. Hinton, Graham W. Taylor, Ilya Sutskever, 2008, NIPS.

Mastering the game of Go with deep neural networks and tree search

Demis Hassabis, Koray Kavukcuoglu, David Silver, 2016, Nature.

An online sequence-to-sequence model for noisy speech recognition pdf

Navdeep Jaitly, George Tucker, Ilya Sutskever, 2017, ArXiv.

Language Models are Unsupervised Multitask Learners

Ilya Sutskever, Alec Radford, David Luan, 2019 .

Learning to Execute pdf

Wojciech Zaremba, Ilya Sutskever, Ilya Sutskever, 2014, ArXiv.

Learning Transferable Visual Models From Natural Language Supervision

Ilya Sutskever, Alec Radford, Gabriel Goh, 2021, ICML.

Zero-Shot Text-to-Image Generation pdf

Ilya Sutskever, Alec Radford, Gabriel Goh, 2021, ICML.

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models pdf

Ilya Sutskever, Prafulla Dhariwal, Bob McGrew, 2021, ArXiv.

Unsupervised Neural Machine Translation with Generative Language Models Only pdf

Ilya Sutskever, Alec Radford, Harrison Edwards, 2021, ArXiv.

Evaluating Large Language Models Trained on Code pdf

Wojciech Zaremba, Lukasz Kaiser, Peter Welinder, 2021, ArXiv.

UTML TR 2011 – 002 Data Normalization in the Learning of Restricted Boltzmann Machines

Ilya Sutskever, Yichuan Tang, Ilya Sutskever, 2011 .

Learning a System-ID Embedding Space for Domain Specialization with Deep Reinforcement Learning

Razvan Pascanu, Peter L. Bartlett, Pieter Abbeel, 2018 .