activity
20242026
collaborators

7 papers

cs.LG2026

DARLING: Detection Augmented Reinforcement Learning with Non-Stationary Guarantees

Argyrios Gerogiannis, Yu-Han Huang, Venugopal V. Veeravalli

We study model-free reinforcement learning (RL) in non-stationary finite-horizon episodic Markov decision processes (MDPs) without prior knowledge of the non-stationarity. We focus…

cs.IT2026

Learning Where to Look: UCB-Driven Controlled Sensing for Quickest Change Detection

Yu-Han Huang, Argyrios Gerogiannis, Subhonmesh Bose +1

We study the multichannel quickest change detection problem with bandit feedback and controlled sensing, in which an agent sequentially selects one of the data streams to observe a…

cs.IT2025

Finite-Horizon Quickest Change Detection Balancing Latency with False Alarm Probability

Yu-Han Huang, Venugopal V. Veeravalli

A finite-horizon variant of the quickest change detection (QCD) problem that is of relevance to learning in non-stationary environments is studied. The metric characterizing false…

cs.IT2025

Sequential Change Detection for Learning in Piecewise Stationary Bandit Environments

Yu-Han Huang, Venugopal V. Veeravalli

A finite-horizon variant of the quickest change detection problem is investigated, which is motivated by a change detection problem that arises in piecewise stationary bandits. The…

cs.AI2025

Detection Augmented Bandit Procedures for Piecewise Stationary MABs: A Modular Approach

Yu-Han Huang, Argyrios Gerogiannis, Subhonmesh Bose +1

Conventional Multi-Armed Bandit (MAB) algorithms are designed for stationary environments, where the reward distributions associated with the arms do not change with time. In many…

cs.LG2024

Is Prior-Free Black-Box Non-Stationary Reinforcement Learning Feasible?

Argyrios Gerogiannis, Yu-Han Huang, Venugopal V. Veeravalli

We study the problem of Non-Stationary Reinforcement Learning (NS-RL) without prior knowledge about the system's non-stationarity. A state-of-the-art, black-box algorithm, known as…

cs.DS2024

High Probability Latency Sequential Change Detection over an Unknown Finite Horizon

Yu-Han Huang, Venugopal V. Veeravalli

A finite horizon variant of the quickest change detection problem is studied, in which the goal is to minimize a delay threshold (latency), under constraints on the probability of…