2 papers
cs.IT2026
Coded Computing for Dynamic System via Cartesian Products
Chenglin Li, Minquan Cheng, Youlong Wu
This paper studies coded distributed computing (CDC) in a dynamic system in which workers may depart and new clusters may join. The caches of the surviving workers and their existi…
cs.LG2024
Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning
Chenglin Li, Guangchun Ruan, Hua Geng
Safe reinforcement learning (RL) is a popular and versatile paradigm to learn reward-maximizing policies with safety guarantees. Previous works tend to express the safety constrain…