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Prabhat Nagarajan
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2020 – today
- 2023
- [i7]Vincent Liu, Prabhat Nagarajan, Andrew Patterson, Martha White:
When is Offline Policy Selection Sample Efficient for Reinforcement Learning? CoRR abs/2312.02355 (2023) - 2021
- [j1]Yasuhiro Fujita, Prabhat Nagarajan, Toshiki Kataoka, Takahiro Ishikawa:
ChainerRL: A Deep Reinforcement Learning Library. J. Mach. Learn. Res. 22: 77:1-77:14 (2021) - [c4]Zhang-Wei Hong, Prabhat Nagarajan, Guilherme Maeda:
Periodic Intra-ensemble Knowledge Distillation for Reinforcement Learning. ECML/PKDD (1) 2021: 87-103 - [c3]Shin-ichi Maeda, Hayato Watahiki, Yi Ouyang, Shintarou Okada, Masanori Koyama, Prabhat Nagarajan:
Reconnaissance for Reinforcement Learning with Safety Constraints. ECML/PKDD (2) 2021: 567-582 - 2020
- [c2]Yasuhiro Fujita, Kota Uenishi, Avinash Ummadisingu, Prabhat Nagarajan, Shimpei Masuda, Mario Ynocente Castro:
Distributed Reinforcement Learning of Targeted Grasping with Active Vision for Mobile Manipulators. IROS 2020: 9712-9719 - [i6]Zhang-Wei Hong, Prabhat Nagarajan, Guilherme Maeda:
Periodic Intra-Ensemble Knowledge Distillation for Reinforcement Learning. CoRR abs/2002.00149 (2020) - [i5]Yasuhiro Fujita, Kota Uenishi, Avinash Ummadisingu, Prabhat Nagarajan, Shimpei Masuda, Mario Ynocente Castro:
Distributed Reinforcement Learning of Targeted Grasping with Active Vision for Mobile Manipulators. CoRR abs/2007.08082 (2020)
2010 – 2019
- 2019
- [c1]Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum:
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. ICML 2019: 783-792 - [i4]Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum:
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. CoRR abs/1904.06387 (2019) - [i3]Yasuhiro Fujita, Toshiki Kataoka, Prabhat Nagarajan, Takahiro Ishikawa:
ChainerRL: A Deep Reinforcement Learning Library. CoRR abs/1912.03905 (2019) - [i2]Aaron J. Havens, Yi Ouyang, Prabhat Nagarajan, Yasuhiro Fujita:
Learning Latent State Spaces for Planning through Reward Prediction. CoRR abs/1912.04201 (2019) - 2018
- [i1]Prabhat Nagarajan, Garrett Warnell, Peter Stone:
Deterministic Implementations for Reproducibility in Deep Reinforcement Learning. CoRR abs/1809.05676 (2018)
Coauthor Index
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