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cs.LG2023
Improving Adaptive Online Learning Using Refined Discretization
Zhiyu Zhang, Heng Yang, Ashok Cutkosky +1
We study unconstrained Online Linear Optimization with Lipschitz losses. Motivated by the pursuit of instance optimality, we propose a new algorithm that simultaneously achieves ($…
cs.LG2023
Unconstrained Dynamic Regret via Sparse Coding
Zhiyu Zhang, Ashok Cutkosky, Ioannis Ch. Paschalidis
Motivated by the challenge of nonstationarity in sequential decision making, we study Online Convex Optimization (OCO) under the coupling of two problem structures: the domain is u…