Jalaj Bhandari

20 papers A* 2A 4Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Structure Enables Effective Self-Localization of Errors in LLMs. CoRR Ankur Samanta, Akshayaa Magesh, Ayush Jain, Kavosh Asadi, Youliang Yu, Daniel Jiang, Boris Vidolov, Kaveh Hassani, Paul Sajda, Jalaj Bhandari, Yonathan Efroni
2025	J	`jnl`	A Note on Code Quality Score: LLMs for Maintainable Large Codebases. CoRR Sherman Wong, Jalaj Bhandari, Leo Zhou Fan Yang, Xylan Xu, Yi Zhuang, Cem Cayiroglu, Payal Bhuptani, Sheela Yadawad, Hung Duong
2025	A*	`conf`	Aligned Multi Objective Optimization. ICML Yonathan Efroni, Ben Kretzu, Daniel Jiang, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich
2025	J	`jnl`	Aligned Multi Objective Optimization. CoRR Yonathan Efroni, Ben Kertzu, Daniel Jiang, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich
2025	J	`jnl`	Aligning LLMs Toward Multi-Turn Conversational Outcomes Using Iterative PPO. CoRR Daniel R. Jiang, Jalaj Bhandari, Yukai Yang, Rémi Munos, Tyler Lu
2024	J	`jnl`	Global Optimality Guarantees for Policy Gradient Methods. Oper. Res. Jalaj Bhandari, Daniel Russo
2024	J	`jnl`	Pearl: A Production-Ready Reinforcement Learning Agent. J. Mach. Learn. Res. 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, Frank Cheng, Zheng Wu, Wanqiao Xu
2023	A	`conf`	Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning. RecSys Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych, Fan Liu, Yuchen He, Alex Nikulkov, Zheqing Zhu
2023	J	`jnl`	Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning. CoRR Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych, Fan Liu, Yuchen He, Alex Nikulkov, Zheqing Zhu
2023	J	`jnl`	Pearl: A Production-ready Reinforcement Learning Agent. CoRR 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, Frank Cheng, Zheng Wu, Wanqiao Xu
2021	J	`jnl`	A Finite Time Analysis of Temporal Difference Learning with Linear Function Approximation. Oper. Res. Jalaj Bhandari, Daniel Russo, Raghav Singal
2021	A	`conf`	On the Linear Convergence of Policy Gradient Methods for Finite MDPs. AISTATS Jalaj Bhandari, Daniel Russo
2020	J	`jnl`	A Note on the Linear Convergence of Policy Gradient Methods. CoRR Jalaj Bhandari, Daniel Russo
2020	—	`—`	Optimization Foundations of Reinforcement Learning. Jalaj Bhandari
2019	J	`jnl`	Global Optimality Guarantees For Policy Gradient Methods. CoRR Jalaj Bhandari, Daniel Russo
2018	A*	`conf`	A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation. COLT Jalaj Bhandari, Daniel Russo, Raghav Singal
2018	J	`jnl`	A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation. CoRR Jalaj Bhandari, Daniel Russo, Raghav Singal
2017	A	`conf`	Annular Augmentation Sampling. AISTATS Francois Fagan, Jalaj Bhandari, John P. Cunningham
2016	A	`conf`	Elliptical Slice Sampling with Expectation Propagation. UAI Francois Fagan, Jalaj Bhandari, John P. Cunningham
2016	J	`jnl`	On the tightness of an LP relaxation for rational optimization and its applications. Oper. Res. Lett. Vashist Avadhanula, Jalaj Bhandari, Vineet Goyal, Assaf Zeevi