| 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 | 5 | 2023 |
| An Optimistic Perspective on Offline Reinforcement Learning R Agarwal, D Schuurmans, M Norouzi International Conference on Machine Learning (ICML), 2020 | 639* | 2020 |
| Behavior Predictive Representations for Generalization in Reinforcement Learning S Agarwal, A Courville, R Agarwal Conference on Reinforcement Learning and Decision Making (RLDM), 2022 | 3 | 2022 |
| Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models A Singh*, JD Co-Reyes*, R Agarwal*, A Anand, P Patil, PJ Liu, J Harrison, ... Transactions on Machine Learning Research (TMLR), 2024 | 36 | 2024 |
| Bigger, Better, Faster: Human-level Atari with human-level efficiency M Schwarzer, JO Ceron, Courville, Bellemare, PS Castro*, R Agarwal* International Conference on Machine Learning (ICML), 2023 | 51 | 2023 |
| Bootstrapped Representations in Reinforcement Learning C Le Lan, S Tu, M Rowland, A Harutyunyan, R Agarwal, MG Bellemare, ... International Conference on Machine Learning (ICML), 2023 | 5 | 2023 |
| 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 | 190 | 2021 |
| Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation E Nikishin, R Abachi, R Agarwal, PL Bacon AAAI Conference on Artificial Intelligence, 2022 | 34 | 2022 |
| 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 | 578 | 2021 |
| Distillspec: Improving speculative decoding via knowledge distillation Y Zhou, K Lyu, AS Rawat, AK Menon, ..., S Kumar, JF Kagy, R Agarwal International Conference on Learning Representations (ICLR), 2024 | 29 | 2024 |
| Don't Throw Away Data: Better Sequence Knowledge Distillation J Wang, E Briakou, H Dadkhahi, R Agarwal, C Cherry, T Cohn arXiv preprint arXiv:2407.10456, 2024 | | 2024 |
| 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 | 52 | 2022 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, *Core Contributor, 2024 | 198 | 2024 |
| Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning A Kumar*, R Agarwal*, D Ghosh, S Levine International Conference on Learning Representations (ICLR), *equal contribution, 2021 | 89 | 2021 |
| 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 | 22 | 2023 |
| Learning and Controlling Silicon Dopant Transitions in Graphene using Scanning Transmission Electron Microscopy M Schwarzer, J Farebrother, J Greaves, ED Cubuk, R Agarwal, ... arXiv preprint arXiv:2311.17894, 2023 | 1* | 2023 |
| Learning to Generalize from Sparse and Underspecified Rewards R Agarwal, C Liang, D Schuurmans, M Norouzi International Conference on Machine Learning (ICML), 2019 | 105 | 2019 |
| Many-shot in-context learning R Agarwal, A Singh, LM Zhang, B Bohnet, S Chan, A Anand, Z Abbas, ... arXiv preprint arXiv:2404.11018, 2024 | 16 | 2024 |
| 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 | 434 | 2021 |
| 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), 𝐍𝐨𝐭𝐚𝐛𝐥𝐞-𝐭𝐨𝐩-𝟓%, 2023 | 39 | 2023 |
Marc G. BellemareReliant AI, prev. Google Brain, DeepMind在 reliant.ai 的电子邮件经过验证
