Ilya Kostrikov

According to our database, Ilya Kostrikov authored at least 34 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning.

Rafael Rafailov, Kyle Beltran Hatch, Anikait Singh, Aviral Kumar, Laura M. Smith, Ilya Kostrikov, Philippe Hansen-Estruch, Victor Kolev, Philip J. Ball, Jiajun Wu, Sergey Levine, Chelsea Finn

RLJ, 2024

Training Diffusion Models with Reinforcement Learning.

Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, Sergey Levine

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, Sergey Levine

CoRR, 2023

Demonstrating A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning.

Ilya Kostrikov, Laura M. Smith, Sergey Levine

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Efficient Online Reinforcement Learning with Offline Data.

Philip J. Ball, Laura M. Smith, Ilya Kostrikov, Sergey Levine

Proceedings of the International Conference on Machine Learning, 2023

Offline RL for Natural Language Generation with Implicit Language Q Learning.

Charlie Snell, Ilya Kostrikov, Yi Su, Sherry Yang, Sergey Levine

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Efficient Deep Reinforcement Learning Requires Regulating Overfitting.

Qiyang Li, Aviral Kumar, Ilya Kostrikov, Sergey Levine

Proceedings of the Eleventh International Conference on Learning Representations, 2023

FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing.

Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar, Ilya Kostrikov, Sergey Levine

Proceedings of the Conference on Robot Learning, 2023

2022

A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning.

Laura M. Smith, Ilya Kostrikov, Sergey Levine

CoRR, 2022

In Defense of the Unitary Scalarization for Deep Multi-Task Learning.

Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, M. Pawan Kumar

CoRR, 2022

Improving Zero-Shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions.

Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

In Defense of the Unitary Scalarization for Deep Multi-Task Learning.

Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, Pawan Kumar Mudigonda

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Offline Reinforcement Learning with Implicit Q-Learning.

Ilya Kostrikov, Ashvin Nair, Sergey Levine

Proceedings of the Tenth International Conference on Learning Representations, 2022

RvS: What is Essential for Offline RL via Supervised Learning?

Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine

Proceedings of the Tenth International Conference on Learning Representations, 2022

Offline Reinforcement Learning for Visual Navigation.

Dhruv Shah, Arjun Bhorkar, Hrishit Leen, Ilya Kostrikov, Nicholas Rhinehart, Sergey Levine

Proceedings of the Conference on Robot Learning, 2022

2021

Improving Sample Efficiency of Imitation and Reinforcement Learning.

Ilya Kostrikov

PhD thesis, 2021

Automatic Data Augmentation for Generalization in Reinforcement Learning.

Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Offline Reinforcement Learning with Fisher Divergence Critic Regularization.

Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum

Proceedings of the 38th International Conference on Machine Learning, 2021

Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels.

Denis Yarats, Ilya Kostrikov, Rob Fergus

Proceedings of the 9th International Conference on Learning Representations, 2021

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images.

Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation.

Ilya Kostrikov, Ofir Nachum

CoRR, 2020

Automatic Data Augmentation for Generalization in Deep Reinforcement Learning.

Roberta Raileanu, Maxwell Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus

CoRR, 2020

Imitation Learning via Off-Policy Distribution Matching.

Ilya Kostrikov, Ofir Nachum, Jonathan Tompson

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

AlgaeDICE: Policy Gradient from Arbitrary Experience.

Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans

CoRR, 2019

Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning.

Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi, Sergey Levine, Jonathan Tompson

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning.

Ilya Kostrikov, Kumar Krishna Agrawal, Sergey Levine, Jonathan Tompson

CoRR, 2018

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play.

Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, Rob Fergus

Proceedings of the 6th International Conference on Learning Representations, 2018

Surface Networks.

Ilya Kostrikov, Zhongshi Jiang, Daniele Panozzo, Denis Zorin, Joan Bruna

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play.

Sainbayar Sukhbaatar, Ilya Kostrikov, Arthur Szlam, Rob Fergus

CoRR, 2017

Surface Networks.

Ilya Kostrikov, Joan Bruna, Daniele Panozzo, Denis Zorin

CoRR, 2017

2016

PlaNet - Photo Geolocation with Convolutional Neural Networks.

Tobias Weyand, Ilya Kostrikov, James Philbin

Proceedings of the Computer Vision - ECCV 2016, 2016

An Efficient Convolutional Network for Human Pose Estimation.

Umer Rafi, Bastian Leibe, Juergen Gall, Ilya Kostrikov

Proceedings of the British Machine Vision Conference 2016, 2016

2014

Probabilistic Labeling Cost for High-Accuracy Multi-view Reconstruction.

Ilya Kostrikov, Esther Horbert, Bastian Leibe

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Depth Sweep Regression Forests for Estimating 3D Human Pose from Images.

Ilya Kostrikov, Jürgen Gall

Proceedings of the British Machine Vision Conference, 2014