Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning. - Riashat Islam; Raihan Seraj; Samin Yeasar Arnob; Doina Precup (CoRR, 2019)

Off-Policy Adversarial Inverse Reinforcement Learning. - Samin Yeasar Arnob (CoRR, 2020)

Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning. - Samin Yeasar Arnob; Riashat Islam; Doina Precup (CoRR, 2021)

Single-Shot Pruning for Offline Reinforcement Learning. - Samin Yeasar Arnob; Riyasat Ohib; Sergey M. Plis; Doina Precup (CoRR, 2021)

Offline Policy Optimization in RL with Variance Regularizaton. - Riashat Islam; Samarth Sinha; Homanga Bharadhwaj; Samin Yeasar Arnob; Zhuoran Yang; Animesh Garg; Zhaoran Wang 001; Lihong Li; Doina Precup (CoRR, 2022)

Representation Learning in Deep RL via Discrete Information Bottleneck. - Riashat Islam; Hongyu Zang; Manan Tomar; Aniket Didolkar; Md Mofijul Islam; Samin Yeasar Arnob; Tariq Iqbal; Xin Li 033; Anirudh Goyal; Nicolas Heess; Alex Lamb (AISTATS, 2023)

Efficient Reinforcement Learning by Discovering Neural Pathways. - Samin Yeasar Arnob; Riyasat Ohib; Sergey M. Plis; Amy Zhang 001; Alessandro Sordoni; Doina Precup (NeurIPS, 2024)

Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity. - Samin Yeasar Arnob; Scott Fujimoto; Doina Precup (CoRR, 2025)

Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts. - Samin Yeasar Arnob; Zhan Su 002; Minseon Kim; Oleksiy Ostapenko; Riyasat Ohib; Esra'a Saleh; Doina Precup; Lucas Caccia; Alessandro Sordoni (CoRR, 2025)