A. Rupam Mahmood

58 papers A* 9A 4B 1Misc 1Journal 43

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AVG-DICE: Stationary Distribution Correction by Regression. CoRR Fengdi Che, Bryan Chan, Chen Ma, A. Rupam Mahmood
2025	J	`jnl`	Distribution Parameter Actor-Critic: Shifting the Agent-Environment Boundary for Diverse Action Spaces. CoRR Jiamin He, A. Rupam Mahmood, Martha White
2025	J	`jnl`	Efficient Reinforcement Learning by Reducing Forgetting with Elephant Activation Functions. CoRR Qingfeng Lan, Gautham Vasan, A. Rupam Mahmood
2025	J	`jnl`	General and Efficient Visual Goal-Conditioned Reinforcement Learning using Object-Agnostic Masks. CoRR Fahim Shahriar, Cheryl Wang, Alireza Azimi, Gautham Vasan, Hany Hamed Elanwar, A. Rupam Mahmood, Colin Bellinger
2025	J	`jnl`	Learning Without Time-Based Embodiment Resets in Soft-Actor Critic. CoRR Homayoon Farrahi, A. Rupam Mahmood
2024	A*	`conf`	Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning. ICLR Mohamed Elsayed, A. Rupam Mahmood
2024	J	`jnl`	Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning. CoRR Mohamed Elsayed, A. Rupam Mahmood
2024	J	`jnl`	Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers. CoRR Gautham Vasan, Mohamed Elsayed, Alireza Azimi, Jiamin He, Fahim Shahriar, Colin Bellinger, Martha White, A. Rupam Mahmood
2024	J	`jnl`	Learning to Optimize for Reinforcement Learning. RLJ Qingfeng Lan, A. Rupam Mahmood, Shuicheng Yan, Zhongwen Xu
2024	J	`jnl`	Loss of plasticity in deep continual learning. Nat. Shibhansh Dohare, J. Fernando Hernandez-Garcia, Qingfeng Lan, Parash Rahman, A. Rupam Mahmood, Richard S. Sutton
2024	A	`conf`	MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. AAMAS Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	J	`jnl`	More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling. RLJ Haque Ishfaq, Yixin Tan, Yu Yang, Qingfeng Lan, Jianfeng Lu, A. Rupam Mahmood, Doina Precup, Pan Xu
2024	J	`jnl`	More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling. CoRR Haque Ishfaq, Yixin Tan, Yu Yang, Qingfeng Lan, Jianfeng Lu, A. Rupam Mahmood, Doina Precup, Pan Xu
2024	A*	`conf`	Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo. ICLR Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli
2024	A*	`conf`	Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning. ICML Mohamed Elsayed, Homayoon Farrahi, Felix Dangel, A. Rupam Mahmood
2024	J	`jnl`	Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning. CoRR Mohamed Elsayed, Homayoon Farrahi, Felix Dangel, A. Rupam Mahmood
2024	J	`jnl`	Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning. RLJ Gautham Vasan, Yan Wang, Fahim Shahriar, James Bergstra, Martin Jägersand, A. Rupam Mahmood
2024	J	`jnl`	Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning. CoRR Gautham Vasan, Yan Wang, Fahim Shahriar, James Bergstra, Martin Jägersand, A. Rupam Mahmood
2024	J	`jnl`	Streaming Deep Reinforcement Learning Finally Works. CoRR Mohamed Elsayed, Gautham Vasan, A. Rupam Mahmood
2024	A*	`conf`	Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. ICML Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
2024	J	`jnl`	Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation. CoRR Fengdi Che, Chenjun Xiao, Jincheng Mei, Bo Dai, Ramki Gummadi, Oscar A. Ramirez, Christopher K. Harris, A. Rupam Mahmood, Dale Schuurmans
2024	J	`jnl`	Weight Clipping for Deep Continual and Reinforcement Learning. RLJ Mohamed Elsayed, Qingfeng Lan, Clare Lyle, A. Rupam Mahmood
2024	J	`jnl`	Weight Clipping for Deep Continual and Reinforcement Learning. CoRR Mohamed Elsayed, Qingfeng Lan, Clare Lyle, A. Rupam Mahmood
2023	A*	`conf`	Correcting discount-factor mismatch in on-policy policy gradient methods. ICML Fengdi Che, Gautham Vasan, A. Rupam Mahmood
2023	J	`jnl`	Correcting discount-factor mismatch in on-policy policy gradient methods. CoRR Fengdi Che, Gautham Vasan, A. Rupam Mahmood
2023	A	`conf`	Dynamic Decision Frequency with Continuous Options. IROS Amirmohammad Karimi, Jun Jin, Jun Luo, A. Rupam Mahmood, Martin Jägersand, Samuele Tosatto
2023	J	`jnl`	Elephant Neural Networks: Born to Be a Continual Learner. CoRR Qingfeng Lan, A. Rupam Mahmood
2023	J	`jnl`	Learning to Optimize for Reinforcement Learning. CoRR Qingfeng Lan, A. Rupam Mahmood, Shuicheng Yan, Zhongwen Xu
2023	A	`conf`	Loosely consistent emphatic temporal-difference learning. UAI Jiamin He, Fengdi Che, Yi Wan, A. Rupam Mahmood
2023	J	`jnl`	MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning. CoRR Bram Grooten, Tristan Tomilin, Gautham Vasan, Matthew E. Taylor, A. Rupam Mahmood, Meng Fang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2023	J	`jnl`	Maintaining Plasticity in Deep Continual Learning. CoRR Shibhansh Dohare, J. Fernando Hernandez-Garcia, Parash Rahman, Richard S. Sutton, A. Rupam Mahmood
2023	J	`jnl`	Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation. Trans. Mach. Learn. Res. Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood
2023	J	`jnl`	Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo. CoRR Haque Ishfaq, Qingfeng Lan, Pan Xu, A. Rupam Mahmood, Doina Precup, Anima Anandkumar, Kamyar Azizzadenesheli
2023	A*	`conf`	Real-Time Reinforcement Learning for Vision-Based Robotics Utilizing Local and Remote Computers. ICRA Yan Wang, Gautham Vasan, A. Rupam Mahmood
2023	B	`conf`	Reducing the Cost of Cycle-Time Tuning for Real-World Policy Optimization. IJCNN Homayoon Farrahi, A. Rupam Mahmood
2023	J	`jnl`	Reducing the Cost of Cycle-Time Tuning for Real-World Policy Optimization. CoRR Homayoon Farrahi, A. Rupam Mahmood
2023	J	`jnl`	Utility-based Perturbed Gradient Descent: An Optimizer for Continual Learning. CoRR Mohamed Elsayed, A. Rupam Mahmood
2022	J	`jnl`	A Temporal-Difference Approach to Policy Gradient Estimation. CoRR Samuele Tosatto, Andrew Patterson, Martha White, A. Rupam Mahmood
2022	A*	`conf`	Asynchronous Reinforcement Learning for Real-Time Control of Physical Robots. ICRA Yufeng Yuan, A. Rupam Mahmood
2022	J	`jnl`	Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences. J. Mach. Learn. Res. Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White
2022	J	`jnl`	HesScale: Scalable Computation of Hessian Diagonals. CoRR Mohamed Elsayed, A. Rupam Mahmood
2022	J	`jnl`	Memory-efficient Reinforcement Learning with Knowledge Consolidation. CoRR Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood
2022	J	`jnl`	Real-Time Reinforcement Learning for Vision-Based Robotics Utilizing Local and Remote Computers. CoRR Yan Wang, Gautham Vasan, A. Rupam Mahmood
2022	J	`jnl`	Variable-Decision Frequency Option Critic. CoRR Amirmohammad Karimi, Jun Jin, Jun Luo, A. Rupam Mahmood, Martin Jägersand, Samuele Tosatto
2021	J	`jnl`	An Alternate Policy Gradient Estimator for Softmax Policies. CoRR Shivam Garg, Samuele Tosatto, Yangchen Pan, Martha White, A. Rupam Mahmood
2021	A*	`conf`	Analyzing Neural Jacobian Methods in Applications of Visual Servoing and Kinematic Control. ICRA Michael Przystupa, Masood Dehghan, Martin Jägersand, A. Rupam Mahmood
2021	J	`jnl`	Analyzing Neural Jacobian Methods in Applications of Visual Servoing and Kinematic Control. CoRR Michael Przystupa, Masood Dehghan, Martin Jägersand, A. Rupam Mahmood
2021	J	`jnl`	Continual Backprop: Stochastic Gradient Descent with Persistent Randomness. CoRR Shibhansh Dohare, A. Rupam Mahmood, Richard S. Sutton
2021	J	`jnl`	Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences. CoRR Alan Chan, Hugo Silva, Sungsu Lim, Tadashi Kozuno, A. Rupam Mahmood, Martha White
2021	J	`jnl`	Model-free Policy Learning with Reward Gradients. CoRR Qingfeng Lan, A. Rupam Mahmood
2020	J	`jnl`	Heteroscedastic Uncertainty for Robust Generative Latent Dynamics. CoRR Oliver Limoyo, Bryan Chan, Filip Maric, Brandon Wagstaff, A. Rupam Mahmood, Jonathan Kelly
2020	J	`jnl`	Heteroscedastic Uncertainty for Robust Generative Latent Dynamics. IEEE Robotics Autom. Lett. Oliver Limoyo, Bryan Chan, Filip Maric, Brandon Wagstaff, A. Rupam Mahmood, Jonathan Kelly
2019	A*	`conf`	Autoregressive Policies for Continuous Control Deep Reinforcement Learning. IJCAI Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan, James Bergstra
2019	J	`jnl`	Autoregressive Policies for Continuous Control Deep Reinforcement Learning. CoRR Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan, James Bergstra
2018	Misc	`conf`	Benchmarking Reinforcement Learning Algorithms on Real-World Robots. CoRL A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra
2018	J	`jnl`	Benchmarking Reinforcement Learning Algorithms on Real-World Robots. CoRR A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra
2018	A	`conf`	Setting up a Reinforcement Learning Task with a Real-World Robot. IROS A. Rupam Mahmood, Dmytro Korenkevych, Brent J. Komer, James Bergstra
2018	J	`jnl`	Setting up a Reinforcement Learning Task with a Real-World Robot. CoRR A. Rupam Mahmood, Dmytro Korenkevych, Brent J. Komer, James Bergstra