The Cost of Learning Under Multiple Change Points
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The Cost of Learning Under Multiple Change Points
arXiv:2602.11406v2 Announce Type: replace-cross Abstract: We consider an online learning problem in environments with multiple change points. In contrast to the single change point problem that is widely studied using classical "high confidence" detection schemes, the multiple change point environment presents new learning-theoretic and algorithmic challenges. Specifically, we show that classical methods may exhibit catastrophic failure (high regret) due to a phenomenon we refer to as...
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