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Rishabh Agarwal
Rishabh Agarwal
Senior Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
An Optimistic Perspective on Offline Reinforcement Learning
R Agarwal, D Schuurmans, M Norouzi
International Conference on Machine Learning (ICML), 2020
369*2020
Neural additive models: Interpretable machine learning with neural nets
R Agarwal, L Melnick, Frosst, Zhang, Lengerich, R Caruana, GE Hinton
Neural Information Processing Systems (NeurIPS), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2021
1902021
Deep Reinforcement Learning at the Edge of the Statistical Precipice
R Agarwal, M Schwarzer, PS Castro, A Courville, MG Bellemare
Neural Information Processing Systems (NeurIPS), 𝗢𝘂𝘁𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗣𝗮𝗽𝗲𝗿 𝗔𝘄𝗮𝗿𝗱, 2021
1682021
Revisiting Fundamentals of Experience Replay
W Fedus*, P Ramachandran*, R Agarwal, Y Bengio, H Larochelle, ...
International Conference on Machine Learning (ICML), 2020
1232020
RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning
C Gulcehre, Z Wang, A Novikov, T Paine, S Gómez, K Zolna, R Agarwal, ...
Advances in Neural Information Processing Systems (NeurIPS), 2020
100*2020
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning
R Agarwal, MC Machado, PS Castro, MG Bellemare
International Conference on Learning Representations (ICLR), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2021
972021
Learning to Generalize from Sparse and Underspecified Rewards
R Agarwal, C Liang, D Schuurmans, M Norouzi
International Conference on Machine Learning (ICML), 2019
832019
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
R Agarwal*, A Kumar*, D Ghosh, S Levine
International Conference on Learning Representations (ICLR), *equal contribution, 2021
40*2021
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization
A Kumar, R Agarwal, T Ma, A Courville, G Tucker, S Levine
International Conference on Learning Representations (ICLR), 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁, 2022
162022
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
E Nikishin, R Abachi, R Agarwal, PL Bacon
AAAI Conference on Artificial Intelligence, 2022
162022
On the Generalization of Representations in Reinforcement Learning
CL Lan, S Tu, A Oberman, R Agarwal, MG Bellemare
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
52022
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress
R Agarwal, M Schwarzer, PS Castro, A Courville, MG Bellemare
Neural Information Processing Systems (NeurIPS), 2022
2*2022
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning
AA Taiga, R Agarwal, J Farebrother, A Courville, MG Bellemare
International Conference on Learning Representations (ICLR), 2023
2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces
CL Lan, J Greaves, J Farebrother, M Rowland, F Pedregosa, R Agarwal, ...
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
2023
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
J Farebrother, J Greaves, R Agarwal, C Le Lan, R Goroshin, PS Castro, ...
International Conference on Learning Representations (ICLR), 2023
2023
Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes
A Kumar, R Agarwal, X Geng, G Tucker, S Levine
International Conference on Learning Representations (ICLR), 𝐎𝐫𝐚𝐥, 2023
2023
Behavior Predictive Representations for Generalization in Reinforcement Learning
S Agarwal, A Courville, R Agarwal
Conference on Reinforcement Learning and Decision Making (RLDM), 2022
2022
Revisiting Bellman Errors for Offline Model Selection
JP Zitovsky, R Agarwal, D de Marchi, MR Kosorok
3rd Offline RL Workshop: Offline RL as a''Launchpad'', 0
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Articles 1–18