4 citations · 9 across the 15 of their papers we have counts for
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Exploiting Adjacent Similarity in Multi-Armed Bandit Tasks via Transfer of Reward Samples
NR Rahul, Vaibhav Katewa
We consider a sequential multi-task problem, where each task is modeled as the stochastic multi-armed bandit with K arms. We assume the bandit tasks are adjacently similar in the s…
Transfer in Sequential Multi-armed Bandits via Reward Samples
Rahul N R, Vaibhav Katewa
We consider a sequential stochastic multi-armed bandit problem where the agent interacts with bandit over multiple episodes. The reward distribution of the arms remain constant thr…
Robust Adversarial Classification via Abstaining
Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
In this work, we consider a binary classification problem and cast it into a binary hypothesis testing framework, where the observations can be perturbed by an adversary. To improv…
A Fundamental Performance Limitation for Adversarial Classification
Abed AlRahman Al Makdah, Vaibhav Katewa, Fabio Pasqualetti
Despite the widespread use of machine learning algorithms to solve problems of technological, economic, and social relevance, provable guarantees on the performance of these data-d…