11 citations · 64 across the 40 of their papers we have counts for
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stat.ML2018
On Distributed Multi-player Multiarmed Bandit Problems in Abruptly Changing Environment
Lai Wei, Vaibhav Srivastava
We study the multi-player stochastic multiarmed bandit (MAB) problem in an abruptly changing environment. We consider a collision model in which a player receives reward at an arm…
math.OC2018
Scenario Approach for Robust Blackbox Optimization in the Bandit Setting
Shaunak D. Bopardikar, Vaibhav Srivastava
This paper discusses a scenario approach to robust optimization of a blackbox function in a bandit setting. We assume that the blackbox function can be modeled as a Gaussian Proces…
stat.ML2018★ 6 cited
On Abruptly-Changing and Slowly-Varying Multiarmed Bandit Problems
Lai Wei, Vaibhav Srivastava
We study the non-stationary stochastic multiarmed bandit (MAB) problem and propose two generic algorithms, namely, the limited memory deterministic sequencing of exploration and ex…