collaborators
Showing cs.LGShow all

6 papers · 1 filter

cs.LG2026

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability

Yushen Liu, Yin-Jen Chen, Ziyi Chen +4

Many safety-critical control problems are modeled as risk-sensitive partially observable Markov decision processes, where the controller must make decisions from incomplete observa…

cs.LG2026

From Dual Tracking to Clipping: Provably Faster Distributionally Robust Multi-Objective Optimization

Yufeng Yang, Fangning Zhuo, Ziyi Chen +2

Multi-objective optimization (MOO) has received growing attention in applications that require learning under multiple criteria. However, most existing MOO formulations do not expl…

cs.LG2026

Provably Efficient Algorithms for S- and Non-Rectangular Robust MDPs with General Parameterization

Anirudh Satheesh, Ziyi Chen, Furong Huang +1

We study robust Markov decision processes (RMDPs) with general policy parameterization under s-rectangular and non-rectangular uncertainty sets. Prior work is largely limited to ta…

cs.LG2025

Trade-off in Estimating the Number of Byzantine Clients in Federated Learning

Ziyi Chen, Su Zhang, Heng Huang

Federated learning has attracted increasing attention at recent large-scale optimization and machine learning research and applications, but is also vulnerable to Byzantine clients…

cs.LG2025

Achieve Performatively Optimal Policy for Performative Reinforcement Learning

Ziyi Chen, Heng Huang

Performative reinforcement learning is an emerging dynamical decision making framework, which extends reinforcement learning to the common applications where the agent's policy can…

cs.LG2025

Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness

Qi He, Peiran Yu, Ziyi Chen +1

Shuffling-type gradient methods are favored in practice for their simplicity and rapid empirical performance. Despite extensive development of convergence guarantees under various…