A. Rupam Mahmood

14 papers · 2014–2024 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🗺️ Taxonomy Completionist (18) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird

🧬 Topic Evolution 🔬 Deep Specialist (10) 👑 Triple Crown ⚡ Prolific Year · Productive 💎 Century Club · Bronze 🗃️ Keyword Collector (63) 📈 Trend Setter

Venues

JMLR (4) ICML (3) ICLR (2) NeurIPS (2) CoRL (1) IJCAI (1) UAI (1)

Top co-authors

Richard S. Sutton (4) Gautham Vasan (4) Martha White (3) Mohamed Elsayed (3) Fengdi Che (3) James Bergstra (2) Dmytro Korenkevych (2) Jiamin He (2) Sungsu Lim (1) Yi Wan (1)

Research topics

Reinforcement Learning (13) Methods (13) Machine Learning (12) Optimization & Theory (10) Applications (5) Learning Types (5) Artificial Intelligence (1) Deep Learning (1) Robotics (1) Bayesian & Probabilistic (1) Capabilities (1) Core AI (1) Techniques (1)

Keywords

reinforcement learning (7) off-policy learning (4) temporal difference learning (4) function approximation (4) value function (3) policy gradient (2) continuous control (2) eligibility trace (2) incremental learning (1) kl divergence (1) sample efficiency (1) robotic manipulation (1) catastrophic forgetting (1) markov chain monte carlo (1) discount factor (1) policy optimization (1) importance sampling (1) bellman equation (1) markov decision process (1) online learning (1)

Papers

Addressing Loss of Plasticity and Catastrophic Forgetting in Continual Learning ICLR 2024 Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers NeurIPS 2024 Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo ICLR 2024 Revisiting Scalable Hessian Diagonal Approximations for Applications in Reinforcement Learning ICML 2024 Target Networks and Over-parameterization Stabilize Off-policy Bootstrapping with Function Approximation ICML 2024 Correcting discount-factor mismatch in on-policy policy gradient methods ICML 2023 Loosely consistent emphatic temporal-difference learning UAI 2023 Greedification Operators for Policy Optimization: Investigating Forward and Reverse KL Divergences JMLR 2022 Autoregressive Policies for Continuous Control Deep Reinforcement Learning IJCAI 2019 Benchmarking Reinforcement Learning Algorithms on Real-World Robots CoRL 2018 On Generalized Bellman Equations and Temporal-Difference Learning JMLR 2018 An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016 True Online Temporal-Difference Learning JMLR 2016 Weighted importance sampling for off-policy learning with linear function approximation NeurIPS 2014