6 citations · 10 across the 17 of their papers we have counts for
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cs.LG2022
Distributed Linear Bandits under Communication Constraints
Sudeep Salgia, Qing Zhao
We consider distributed linear bandits where agents learn collaboratively to minimize the overall cumulative regret incurred by all agents. Information exchange is facilitated…
stat.ML2022
Collaborative Learning in Kernel-based Bandits for Distributed Users
Sudeep Salgia, Sattar Vakili, Qing Zhao
We study collaborative learning among distributed clients facilitated by a central server. Each client is interested in maximizing a personalized objective function that is a weigh…
stat.ML2022★ 1 cited
Provably and Practically Efficient Neural Contextual Bandits
Sudeep Salgia, Sattar Vakili, Qing Zhao
We consider the neural contextual bandit problem. In contrast to the existing work which primarily focuses on ReLU neural nets, we consider a general set of smooth activation funct…