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News/Bandit PCA with Minimax Optimal Regret
arxiv
PublishedJuly 16, 2026 at 4:00 AM
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Bandit PCA with Minimax Optimal Regret

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arXiv:2607.10936v2 Announce Type: replace Abstract: We study the bandit-feedback version of online principal component analysis (Bandit PCA): in each round $t = 1,\dots,T$, the adversary selects a $d \times d$ symmetric gain matrix $G_t$ with spectrum in $[0,1]$ and rank at most $r$; the learner sim

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