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From Switching to Dynamic Regret: A Simple Reduction via Unbiased Random Sequences

arXiv:2609.20968v1 Announce Type: new Abstract: In non-stationary online learning, dynamic regret has attracted increasing attention as a measure of how well an online learner performs against a time-varying comparator sequence. Despite considerable advances, attaining optimal bounds for strongly c…

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  1. 2026-09-21 04:00 · arXiv cs.LG
    From Switching to Dynamic Regret: A Simple Reduction via Unbiased Random Sequences

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