Elliptical Slice Sampling with Expectation Propagation. - Francois Fagan; Jalaj Bhandari; John P. Cunningham (UAI, 2016)

On the tightness of an LP relaxation for rational optimization and its applications. - Vashist Avadhanula; Jalaj Bhandari; Vineet Goyal; Assaf Zeevi (Oper. Res. Lett., 2016)

Annular Augmentation Sampling. - Francois Fagan; Jalaj Bhandari; John P. Cunningham (AISTATS, 2017)

A Note on the Linear Convergence of Policy Gradient Methods. - Jalaj Bhandari; Daniel Russo 001 (CoRR, 2020)

Optimization Foundations of Reinforcement Learning. - Jalaj Bhandari (2020)

On the Linear Convergence of Policy Gradient Methods for Finite MDPs. - Jalaj Bhandari; Daniel Russo 001 (AISTATS, 2021)

A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation. - Jalaj Bhandari; Daniel Russo 001; Raghav Singal (Oper. Res., 2021)

Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning. - Ruiyang Xu; Jalaj Bhandari; Dmytro Korenkevych; Fan Liu; Yuchen He 002; Alex Nikulkov; Zheqing Zhu (RecSys, 2023)

Pearl: A Production-ready Reinforcement Learning Agent. - Zheqing Zhu; Rodrigo de Salvo Braz; Jalaj Bhandari; Daniel Jiang; Yi Wan; Yonathan Efroni; Liyuan Wang; Ruiyang Xu; Hongbo Guo; Alex Nikulkov; Dmytro Korenkevych; Ürün Dogan; et al. (CoRR, 2023)

Global Optimality Guarantees for Policy Gradient Methods. - Jalaj Bhandari; Daniel Russo 001 (Oper. Res., 2024)

Aligned Multi Objective Optimization. - Yonathan Efroni; Ben Kertzu; Daniel Jiang; Jalaj Bhandari; Zheqing Zhu; Karen Ullrich (CoRR, 2025)

A Note on Code Quality Score: LLMs for Maintainable Large Codebases. - Sherman Wong; Jalaj Bhandari; Leo Zhou Fan Yang; Xylan Xu; Yi Zhuang; Cem Cayiroglu; Payal Bhuptani; Sheela Yadawad; Hung Duong (CoRR, 2025)