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cs.LG2025
Dual Adaptivity: Universal Algorithms for Minimizing the Adaptive Regret of Convex Functions
Lijun Zhang, Wenhao Yang, Guanghui Wang +2
To deal with changing environments, a new performance measure -- adaptive regret, defined as the maximum static regret over any interval, was proposed in online learning. Under the…
cs.LG2020★ 3 cited
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs
Bo Xue, Guanghui Wang, Yimu Wang +1
In this paper, we study the problem of stochastic linear bandits with finite action sets. Most of existing work assume the payoffs are bounded or sub-Gaussian, which may be violate…