4 papers
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…
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…
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…
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…