116 citations · 1k across the 78 of their papers we have counts for
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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…
Principled Detection of Hallucinations in Large Language Models via Multiple Testing
Jiawei Li, Akshayaa Magesh, Venugopal V. Veeravalli
While Large Language Models (LLMs) have emerged as powerful foundational models to solve a variety of tasks, they have also been shown to be prone to hallucinations, i.e., generati…
Heterogeneous Multi-Player Multi-Armed Bandits Robust To Adversarial Attacks
Akshayaa Magesh, Venugopal V. Veeravalli
We consider a multi-player multi-armed bandit setting in the presence of adversaries that attempt to negatively affect the rewards received by the players in the system. The reward…
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…