Mahmood, A. Rupam

19 publications

ICLR 2024 Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning Mohamed Elsayed, A. Rupam Mahmood

NeurIPS 2024 Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers Gautham Vasan, Mohamed Elsayed, Alireza Azimi, Jiamin He, Fahim Shariar, Colin Bellinger, Martha White, A. Rupam Mahmood

NeurIPSW 2024 Deep Reinforcement Learning Without Experience Replay, Target Networks, or Batch Updates Mohamed Elsayed, Gautham Vasan, A. Rupam Mahmood

ICLR 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli

ICML 2024 Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning Mohamed Elsayed, Homayoon Farrahi, Felix Dangel, A. Rupam Mahmood

ICML 2024 Target Networks and Over-Parameterization Stabilize Off-Policy Bootstrapping with Function Approximation Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A Ramirez, Christopher K Harris, A. Rupam Mahmood, Dale Schuurmans

ICML 2023 Correcting Discount-Factor Mismatch in On-Policy Policy Gradient Methods Fengdi Che, Gautham Vasan, A. Rupam Mahmood

UAI 2023 Loosely Consistent Emphatic Temporal-Difference Learning Jiamin He, Fengdi Che, Yi Wan, A. Rupam Mahmood

TMLR 2023 Memory-Efficient Reinforcement Learning with Value-Based Knowledge Consolidation Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood

NeurIPSW 2023 Utility-Based Perturbed Gradient Descent: An Optimizer for Continual Learning Mohamed Elsayed, A. Rupam Mahmood

JMLR 2022 Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White

NeurIPSW 2022 The Emphatic Approach to Average-Reward Policy Evaluation Jiamin He, Yi Wan, A. Rupam Mahmood

NeurIPSW 2022 The Emphatic Approach to Average-Reward Policy Evaluation Jiamin He, Yi Wan, A. Rupam Mahmood

IJCAI 2019 Autoregressive Policies for Continuous Control Deep Reinforcement Learning Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan, James Bergstra

CoRL 2018 Benchmarking Reinforcement Learning Algorithms on Real-World Robots A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra

JMLR 2018 On Generalized Bellman Equations and Temporal-Difference Learning Huizhen Yu, A. Rupam Mahmood, Richard S. Sutton

JMLR 2016 An Emphatic Approach to the Problem of Off-Policy Temporal-Difference Learning Richard S. Sutton, A. Rupam Mahmood, Martha White

JMLR 2016 True Online Temporal-Difference Learning Harm van Seijen, A. Rupam Mahmood, Patrick M. Pilarski, Marlos C. Machado, Richard S. Sutton

NeurIPS 2014 Weighted Importance Sampling for Off-Policy Learning with Linear Function Approximation A. Rupam Mahmood, Hado P van Hasselt, Richard S. Sutton