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Cosmin Paduraru
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2020 – today
- 2024
- [i16]Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust:
Training Language Models to Self-Correct via Reinforcement Learning. CoRR abs/2409.12917 (2024) - 2023
- [j2]Daniel J. Mankowitz
, Andrea Michi
Faster sorting algorithms discovered using deep reinforcement learning. Nat. 618(7964): 257-263 (2023) - [c10]Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru:
Transformers Meet Directed Graphs. ICML 2023: 11144-11172 - [i15]Simon Geisler, Yujia Li, Daniel J. Mankowitz, Ali Taylan Cemgil, Stephan Günnemann, Cosmin Paduraru:
Transformers Meet Directed Graphs. CoRR abs/2302.00049 (2023) - [i14]Pengming Wang, Mikita Sazanovich, Berkin Ilbeyi, Phitchaya Mangpo Phothilimthana, Manish Purohit, Han Yang Tay, Ngân Vu, Miaosen Wang, Cosmin Paduraru, Edouard Leurent, Anton Zhernov, Julian Schrittwieser, Thomas Hubert, Robert Tung, Paula Kurylowicz, Kieran Milan, Oriol Vinyals, Daniel J. Mankowitz:
Optimizing Memory Mapping Using Deep Reinforcement Learning. CoRR abs/2305.07440 (2023) - [i13]Brendan D. Tracey, Andrea Michi, Yuri Chervonyi, Ian Davies, Cosmin Paduraru, Nevena Lazic, Federico Felici, Timo Ewalds, Craig Donner, Cristian Galperti, Jonas Buchli, Michael Neunert, Andrea Huber, Jonathan Evens, Paula Kurylowicz, Daniel J. Mankowitz, Martin A. Riedmiller, The TCV Team:
Towards practical reinforcement learning for tokamak magnetic control. CoRR abs/2307.11546 (2023) - 2022
- [c9]Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez:
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. ICLR 2022 - [i12]Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez:
COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. CoRR abs/2204.08957 (2022) - [i11]Yuri Chervonyi, Praneet Dutta, Piotr Trochim, Octavian Voicu, Cosmin Paduraru, Crystal Qian, Emre Karagozler, Jared Quincy Davis, Richard Chippendale, Gautam Bajaj, Sims Witherspoon, Jerry Luo:
Semi-analytical Industrial Cooling System Model for Reinforcement Learning. CoRR abs/2207.13131 (2022) - [i10]William Wong, Praneet Dutta, Octavian Voicu, Yuri Chervonyi, Cosmin Paduraru, Jerry Luo:
Optimizing Industrial HVAC Systems with Hierarchical Reinforcement Learning. CoRR abs/2209.08112 (2022) - [i9]Jerry Luo, Cosmin Paduraru, Octavian Voicu, Yuri Chervonyi, Scott Munns, Jerry Li, Crystal Qian, Praneet Dutta, Jared Quincy Davis, Ningjia Wu, Xingwei Yang, Chu-Ming Chang, Ted Li, Rob Rose
Controlling Commercial Cooling Systems Using Reinforcement Learning. CoRR abs/2211.07357 (2022) - 2021
- [j1]Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester:
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. Mach. Learn. 110(9): 2419-2468 (2021) - [c8]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. ICLR 2021 - [c7]Michael R. Zhang, Thomas Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi:
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. ICLR 2021 - [c6]Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. NeurIPS 2021: 24631-24644 - [i8]Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine:
Benchmarks for Deep Off-Policy Evaluation. CoRR abs/2103.16596 (2021) - [i7]Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi:
Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. CoRR abs/2104.13877 (2021) - [i6]Ksenia Konyushkova, Yutian Chen, Thomas Paine, Çaglar Gülçehre, Cosmin Paduraru, Daniel J. Mankowitz, Misha Denil, Nando de Freitas:
Active Offline Policy Selection. CoRR abs/2106.10251 (2021) - 2020
- [c5]Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Thomas Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matthew Hoffman, Nicolas Heess, Nando de Freitas:
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. NeurIPS 2020 - [i5]Gabriel Dulac-Arnold, Nir Levine, Daniel J. Mankowitz, Jerry Li, Cosmin Paduraru, Sven Gowal, Todd Hester:
An empirical investigation of the challenges of real-world reinforcement learning. CoRR abs/2003.11881 (2020) - [i4]Çaglar Gülçehre, Ziyu Wang, Alexander Novikov, Tom Le Paine, Sergio Gómez Colmenarejo, Konrad Zolna, Rishabh Agarwal, Josh Merel, Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Jerry Li, Mohammad Norouzi, Matt Hoffman, Ofir Nachum, George Tucker, Nicolas Heess, Nando de Freitas:
RL Unplugged: Benchmarks for Offline Reinforcement Learning. CoRR abs/2006.13888 (2020) - [i3]Tom Le Paine, Cosmin Paduraru, Andrea Michi, Çaglar Gülçehre, Konrad Zolna, Alexander Novikov, Ziyu Wang, Nando de Freitas:
Hyperparameter Selection for Offline Reinforcement Learning. CoRR abs/2007.09055 (2020) - [i2]Daniel J. Mankowitz, Dan A. Calian, Rae Jeong, Cosmin Paduraru, Nicolas Heess, Sumanth Dathathri, Martin A. Riedmiller, Timothy A. Mann:
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/2010.10644 (2020)
2010 – 2019
- 2018
- [i1]Gal Dalal, Krishnamurthy Dvijotham, Matej Vecerík, Todd Hester, Cosmin Paduraru, Yuval Tassa:
Safe Exploration in Continuous Action Spaces. CoRR abs/1801.08757 (2018) - 2012
- [c4]Cosmin Paduraru, Doina Precup, Joelle Pineau, Gheorghe Comanici:
An Empirical Analysis of Off-policy Learning in Discrete MDPs. EWRL 2012: 89-102 - 2011
- [c3]Cosmin Paduraru, Doina Precup, Joelle Pineau:
A Framework for Computing Bounds for the Return of a Policy. EWRL 2011: 201-212
2000 – 2009
- 2007
- [c2]Brian Tanner, Vadim Bulitko, Anna Koop, Cosmin Paduraru:
Grounding Abstractions in Predictive State Representations. IJCAI 2007: 1077-1082 - 2005
- [c1]Doina Precup, Richard S. Sutton, Cosmin Paduraru, Anna Koop, Satinder Singh:
Off-policy Learning with Options and Recognizers. NIPS 2005: 1097-1104
Coauthor Index
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