Publications [#356438] of Cynthia D. Rudin

Papers Published

1. Wang, T; Rudin, C, Bandits for bmo functions, 37th International Conference on Machine Learning, ICML 2020, vol. PartF168147-13 (January, 2020), pp. 9938-9948, ISBN 9781713821120
   (last updated on 2024/04/16)

   Abstract:
   We study the bandit problem where the underlying expected reward is a Bounded Mean Oscillation (BMO) function. BMO functions are allowed to be discontinuous and unbounded, and are useful in modeling signals with infinities in the domain. We develop a toolset for BMO bandits, and provide an algorithm that can achieve poly-log-regret a regret measured against an arm that is optimal after removing a-sized portion of the arm space.