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Strongly-polynomial time and validation analysis of policy gradient methods
Caleb Ju and Guanghui Lan (α)
Submitted
📌 The Alice and John Jarvis Best Paper Award (2025)Policy optimization over general state and action spaces
Caleb Ju and Guanghui Lan (α)
Under revisionDual dynamic programming for stochastic programs over an infinite horizon
Caleb Ju and Guanghui Lan
Submitted
📌 MOPTA Best Poster Award (2023)Learning a Local Trading Strategy: Deep Reinforcement Learning for Grid-scale Renewable Energy Integration
Caleb Ju and Constance Crozier
Hawaii International Conference on System Sciences 2025
📰 Featured in DEIXISReinforcement Learning-Based Control for Waste Biorefining Processes Under Uncertainty
Ji Gao, Abigael Whalen, Caleb Ju, Yongsheng Chen, Guanghui Lan, Zhaohui Tong
Communications Engineering[arXiv]Efficient parallel implementation of the multiplicative weight update method for graph-based linear programs
Caleb Ju, Serif Yesil, Mengyuan Sun, Chandra Chekuri, Edgar Solomonik
Pre-print[arXiv]Implicit regularization of Bregman proximal point algorithm and mirror descent on separable data
Yan Li, Caleb Ju, Ethan X. Fang, Tuo Zhao
Pre-printCommunication lower bounds for nested bilinear algorithms via rank expansion of Kronecker products
Caleb Ju*, Yifan Zhang*, Edgar Solomonik
Foundations of Computational Mathematics