3 papers
eess.SY2025
A Control Theory inspired Exploration Method for a Linear Bandit driven by a Linear Gaussian Dynamical System
Jonathan Gornet, Yilin Mo, Bruno Sinopoli
The paper introduces a linear bandit environment where the reward is the output of a known Linear Gaussian Dynamical System (LGDS). In this environment, we address the fundamental…
cs.LG2025
An Exploration-free Method for a Linear Stochastic Bandit Driven by a Linear Gaussian Dynamical System
Jonathan Gornet, Yilin Mo, Bruno Sinopoli
In stochastic multi-armed bandits, a major problem the learner faces is the trade-off between exploration and exploitation. Recently, exploration-free methods -- methods that commi…
math.OC2025
Almost Surely Regret for Adaptive LQR
Yiwen Lu, Yilin Mo
The Linear-Quadratic Regulation (LQR) problem with unknown system parameters has been widely studied, but it has remained unclear whether regret, w…