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2020 – today
- 2022
[i16]Vitaly Kurin, Alessandro De Palma, Ilya Kostrikov, Shimon Whiteson, M. Pawan Kumar:
In Defense of the Unitary Scalarization for Deep Multi-Task Learning. CoRR abs/2201.04122 (2022)- [i15]Charlie Snell, Ilya Kostrikov, Yi Su, Mengjiao Yang, Sergey Levine:
Offline RL for Natural Language Generation with Implicit Language Q Learning. CoRR abs/2206.11871 (2022) - 2021
- [b1]Ilya Kostrikov:
Improving Sample Efficiency of Imitation and Reinforcement Learning. New York University, USA, 2021 - [c12]Denis Yarats, Amy Zhang, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. AAAI 2021: 10674-10681 - [c11]Denis Yarats, Ilya Kostrikov, Rob Fergus:
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. ICLR 2021 - [c10]Ilya Kostrikov, Rob Fergus, Jonathan Tompson, Ofir Nachum:
Offline Reinforcement Learning with Fisher Divergence Critic Regularization. ICML 2021: 5774-5783 - [c9]Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Reinforcement Learning. NeurIPS 2021: 5402-5415 - [i14]Ilya Kostrikov, Jonathan Tompson, Rob Fergus, Ofir Nachum:
Offline Reinforcement Learning with Fisher Divergence Critic Regularization. CoRR abs/2103.08050 (2021) - [i13]Ilya Kostrikov, Ashvin Nair, Sergey Levine:
Offline Reinforcement Learning with Implicit Q-Learning. CoRR abs/2110.06169 (2021) - [i12]Bogdan Mazoure, Ilya Kostrikov, Ofir Nachum, Jonathan Tompson:
Improving Zero-shot Generalization in Offline Reinforcement Learning using Generalized Similarity Functions. CoRR abs/2111.14629 (2021) - [i11]Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine:
RvS: What is Essential for Offline RL via Supervised Learning? CoRR abs/2112.10751 (2021) - 2020
- [c8]Ilya Kostrikov, Ofir Nachum, Jonathan Tompson:
Imitation Learning via Off-Policy Distribution Matching. ICLR 2020 - [i10]Ilya Kostrikov, Denis Yarats, Rob Fergus:
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels. CoRR abs/2004.13649 (2020) - [i9]Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus:
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning. CoRR abs/2006.12862 (2020) - [i8]Ilya Kostrikov, Ofir Nachum:
Statistical Bootstrapping for Uncertainty Estimation in Off-Policy Evaluation. CoRR abs/2007.13609 (2020)
2010 – 2019
- 2019
- [c7]Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi, Sergey Levine, Jonathan Tompson:
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning. ICLR (Poster) 2019 - [i7]Denis Yarats, Amy Zhang
, Ilya Kostrikov, Brandon Amos, Joelle Pineau, Rob Fergus:
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images. CoRR abs/1910.01741 (2019) - [i6]Ofir Nachum, Bo Dai, Ilya Kostrikov, Yinlam Chow, Lihong Li, Dale Schuurmans:
AlgaeDICE: Policy Gradient from Arbitrary Experience. CoRR abs/1912.02074 (2019) - [i5]Ilya Kostrikov, Ofir Nachum, Jonathan Tompson:
Imitation Learning via Off-Policy Distribution Matching. CoRR abs/1912.05032 (2019) - 2018
- [c6]Ilya Kostrikov, Zhongshi Jiang, Daniele Panozzo, Denis Zorin, Joan Bruna:
Surface Networks. CVPR 2018: 2540-2548 - [c5]Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, Rob Fergus:
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. ICLR (Poster) 2018 - [i4]Ilya Kostrikov, Kumar Krishna Agrawal, Sergey Levine, Jonathan Tompson:
Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning. CoRR abs/1809.02925 (2018) - 2017
- [i3]Sainbayar Sukhbaatar, Ilya Kostrikov, Arthur Szlam, Rob Fergus:
Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play. CoRR abs/1703.05407 (2017) - [i2]Ilya Kostrikov, Joan Bruna, Daniele Panozzo, Denis Zorin:
Surface Networks. CoRR abs/1705.10819 (2017) - 2016
- [c4]Umer Rafi, Bastian Leibe, Juergen Gall, Ilya Kostrikov:
An Efficient Convolutional Network for Human Pose Estimation. BMVC 2016 - [c3]Tobias Weyand, Ilya Kostrikov, James Philbin:
PlaNet - Photo Geolocation with Convolutional Neural Networks. ECCV (8) 2016: 37-55 - [i1]Tobias Weyand, Ilya Kostrikov, James Philbin:
PlaNet - Photo Geolocation with Convolutional Neural Networks. CoRR abs/1602.05314 (2016) - 2014
- [c2]Ilya Kostrikov, Jürgen Gall:
Depth Sweep Regression Forests for Estimating 3D Human Pose from Images. BMVC 2014 - [c1]Ilya Kostrikov, Esther Horbert, Bastian Leibe:
Probabilistic Labeling Cost for High-Accuracy Multi-view Reconstruction. CVPR 2014: 1534-1541
Coauthor Index
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