2 citations · 2 across the 6 of their papers we have counts for
6 papers
LEAF: Growing Trees Without Branching for Speech-Aware Large Language Model Post-Training
Argyrios Gerogiannis, Yekaterina Yegorova, Mark Hasegawa-Johnson +1
State-of-the-art GRPO-style methods for speech-aware large language model post-training suffer from coarse credit assignment, broadcasting the same terminal-reward advantage to eve…
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…
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…
DAL: A Practical Prior-Free Black-Box Framework for Piecewise Stationary Bandits
Argyrios Gerogiannis, Yu-Han Huang, Subhonmesh Bose +1
We introduce a practical, black-box framework termed Detection Augmented Learning (DAL) for the problem of piecewise stationary bandits without knowledge of the underlying non-stat…
Quickest Change Detection with Controlled Sensing
Venugopal V. Veeravalli, Georgios Fellouris, George V. Moustakides
In the problem of quickest change detection, a change occurs at some unknown time in the distribution of a sequence of random vectors that are monitored in real time, and the goal…
Data-Efficient Quickest Change Detection with On-Off Observation Control
Taposh Banerjee, Venugopal V. Veeravalli
In this paper we extend the Shiryaev's quickest change detection formulation by also accounting for the cost of observations used before the change point. The observation cost is c…