Ilya Sutskever

发表

ImageNet classification with deep convolutional neural networks

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

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

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

Dropout: a simple way to prevent neural networks from overfitting

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

On the importance of initialization and momentum in deep learning

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

SUBWORD LANGUAGE MODELING WITH NEURAL NETWORKS

Ilya Sutskever, Tomas Mikolov, Anoop Deoras, 2011 .

Using matrices to model symbolic relationships

Geoffrey E. Hinton, Ilya Sutskever, 2008 .

Intriguing properties of neural networks pdf

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

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

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

Continuous Deep Q-Learning with Model-based Acceleration pdf

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

Distribution Augmentation for Generative Modeling

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

Variational Lossy Autoencoder pdf

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

Move Evaluation in Go Using Deep Convolutional Neural Networks pdf

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

Multi-task Sequence to Sequence Learning pdf

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

Neural GPUs Learn Algorithms

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

Adding Gradient Noise Improves Learning for Very Deep Networks pdf

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

Reinforcement Learning Neural Turing Machines pdf

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

Language Models are Unsupervised Multitask Learners

Ilya Sutskever, Alec Radford, David Luan, 2019 .

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

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

Training Deep and Recurrent Networks with Hessian-Free Optimization

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

Distributed Representations of Words and Phrases and their Compositionality pdf

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

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

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

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

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

Sequence to Sequence Learning with Neural Networks

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

Learning Multilevel Distributed Representations for High-Dimensional Sequences

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

GamePad: A Learning Environment for Theorem Proving pdf

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

Towards Principled Unsupervised Learning pdf

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

Estimating the Hessian by Back-propagating Curvature

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

An Empirical Exploration of Recurrent Network Architectures

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

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

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

Learning Recurrent Neural Networks with Hessian-Free Optimization

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

Evolution Strategies as a Scalable Alternative to Reinforcement Learning pdf

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

Recurrent Neural Network Regularization pdf

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

Generating Text with Recurrent Neural Networks

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

Language Models are Few-Shot Learners pdf

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

Learning to Execute pdf

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

Dota 2 with Large Scale Deep Reinforcement Learning pdf

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

Jukebox: A Generative Model for Music pdf

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

Generative Pretraining From Pixels

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

Third-Person Imitation Learning pdf

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

Reinforcement Learning Neural Turing Machines - Revised

Wojciech Zaremba, Ilya Sutskever, Ilya Sutskever, 2015 .

Data Normalization in the Learning of Restricted Boltzmann Machines

Ilya Sutskever, Yichuan Tang, 2011 .

The Recurrent Temporal Restricted Boltzmann Machine

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

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.

Deep, Narrow Sigmoid Belief Networks Are Universal Approximators

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

Learning to Generate Reviews and Discovering Sentiment pdf

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

On the Convergence Properties of Contrastive Divergence

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

Temporal-Kernel Recurrent Neural Networks

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

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

Neural Programmer: Inducing Latent Programs with Gradient Descent pdf

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

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

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

Modelling Relational Data using Bayesian Clustered Tensor Factorization

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

Neural Random Access Machines

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

Deep Neural Networks

Michael Guerzhoy, Ilya Sutskever, Ilya Sutskever, 2013 .

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

Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning

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

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

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

DLVM : A MODERN COMPILER INFRASTRUCTURE FOR DEEP LEARNING

Vincent Vanhoucke, Oriol Vinyals, P. Tucker, 2017 .

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

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

Dota 2 with Large Scale Deep Reinforcement Learning

Jakub W. Pachocki, Henrique Pondé de Oliveira Pinto, F. Wolski, 2019, ArXiv.

HIRD-P ERSON I MITATION L EARNING

Bradly C. Stadie, P. Abbeel, Ilya Sutskever, 2017 .

CSC 2414-Metric Embeddings ∗ Lecture 5 : Dimension Reduction

Ilya Sutskever, Hamed Hatami, 2006 .

32 15 v 3 [ cs . C L ] 1 4 D ec 2 01 4 Sequence to Sequence Learning with Neural Networks

Ilya Sutskever, 2018 .

The Importance of Sampling inMeta-Reinforcement Learning

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

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

Ilya Sutskever, Yichuan Tang, Ilya Sutskever, 2011 .

TensorFlow Distributions Joshua

Andy Davis, Geoffrey Irving, Dandelion Mané, 2017 .

Feature-Matching Auto-Encoders

Ilya Sutskever, Dustin Tran, Yura Burda, 2017 .

Mimicking Go Experts with Convolutional Neural Networks

Ilya Sutskever, Vinod Nair, 2008, ICANN.

Zero-Shot Text-to-Image Generation

Alec Radford, Ilya Sutskever, Mark Chen, 2021, ICML.

Zero-Shot Text-to-Image Generation pdf

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

Conditional Augmentation for Generative Modeling

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

A Closer Look at Gradient Estimators with Reinforcement Learning as Inference

Ilya Sutskever, Jonathon Shlens, C. Olah, 2021 .

Extensions and Limitations of the Neural GPU

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

Robust Speech Recognition via Large-Scale Weak Supervision

Jong Wook Kim, Alec Radford, Ilya Sutskever, 2022, ICML.

MAQA: A Multimodal QA Benchmark for Negation Anonymous Author(s)

Daniel M. Ziegler, Jacob Devlin, Prafulla Dhariwal, 2022 .

Cardinality Restricted Boltzmann Machines

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

Emergent Complexity via Multi-Agent Competition pdf

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

One-Shot Imitation Learning

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

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

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

Learning Transferable Visual Models From Natural Language Supervision

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

Learning Factored Representations in a Deep Mixture of Experts pdf

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

Generating Long Sequences with Sparse Transformers pdf

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

Grammar as a Foreign Language

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

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

Prafulla Dhariwal, Ilya Sutskever, Alex Nichol, 2021, ICML.

A Neural Transducer

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

Evaluating Large Language Models Trained on Code pdf

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

Consistency Models

Prafulla Dhariwal, Ilya Sutskever, Mark Chen, 2023, ArXiv.

MuProp: Unbiased Backpropagation for Stochastic Neural Networks pdf

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

Formal Mathematics Statement Curriculum Learning

Jesse Michael Han, I. Babuschkin, Ilya Sutskever, 2022, ICLR.

Generative Language Modeling for Automated Theorem Proving pdf

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

Generating Text with Recurrent Neural Networks

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

An Online Sequence-to-Sequence Model Using Partial Conditioning

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

Unsupervised Neural Machine Translation with Generative Language Models Only pdf

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

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

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

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).

Rethinking the modeling of the instrumental response of telescopes with a differentiable optical model

Ilya Sutskever, Jonathon Shlens, Sherry Moore, 2021 .

Using matrices to model symbolic relationship

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

Let's Verify Step by Step

J. Schulman, Ilya Sutskever, Karl Cobbe, 2023, ArXiv.

Improving neural networks by preventing co-adaptation of feature detectors

Geoffrey E. Hinton, R. Salakhutdinov, A. Krizhevsky, 2012, ArXiv.

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

J. Schulman, P. Abbeel, Rein Houthooft, 2016, NIPS.

A simpler unified analysis of budget perceptrons

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

Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments

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

Consistency Models

Prafulla Dhariwal, Ilya Sutskever, Mark Chen, 2023, ICML.

GamePad: A Learning Environment for Theorem Proving

Prafulla Dhariwal, D. Song, Ilya Sutskever, 2018, ICLR.

Improving Variational Autoencoders with Inverse Autoregressive Flow

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

Number 20

Geoffrey E. Hinton, A. Krizhevsky, Ilya Sutskever, 1998 .

Trustless Machine Learning Contracts; Evaluating and Exchanging Machine Learning Models on the Ethereum Blockchain pdf

A. Besir Kurtulmus, Kenny Daniel, A. Krizhevsky, 2018, ArXiv.

RL: FAST REINFORCEMENT LEARNING VIA SLOW REINFORCEMENT LEARNING

J. Schulman, P. Abbeel, P. Bartlett, 2016 .

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

Chris J. Maddison, George van den Driessche, Aja Huang, 2016, Nature.

Generating Text with Recurrent Neural Networks

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