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cs.LG2026
Learning to Sparsify Stochastic Linear Bandits
Zhengmiao Wang, Ming Chi, Zhi-Wei Liu +2
This paper addresses the problem of learning to sparsify stochastic linear bandits, where a decision-maker sequentially selects actions from a high-dimensional space subject to a s…
cs.LG2026
Online Learning of Kalman Filtering: From Output to State Estimation
Lintao Ye, Ankang Zhang, Ming Chi +2
In this paper, we study the problem of learning Kalman filtering with unknown system model in partially observed linear dynamical systems. We propose a unified algorithmic framewor…
eess.SY2026
Model-Free Output Feedback Stabilization via Policy Gradient Methods
Ankang Zhang, Ming Chi, Xiaoling Wang +1
Stabilizing a dynamical system is a fundamental problem that serves as a cornerstone for many complex tasks in the field of control systems. The problem becomes challenging when th…