Anchor-TS defines arm indices as the median of an online posterior sample, a hybrid posterior sample, and the online sample mean to correct distribution-shift bias and safely accelerate online learning with offline data.
Journal of Machine Learning Research , volume=
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CCBO enables collaborative contextual Bayesian optimization across clients with sublinear regret guarantees and shows substantial gains over non-collaborative methods in simulations and a hot rolling application even under heterogeneity.
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Sample-Mean Anchored Thompson Sampling for Offline-to-Online Learning with Distribution Shift
Anchor-TS defines arm indices as the median of an online posterior sample, a hybrid posterior sample, and the online sample mean to correct distribution-shift bias and safely accelerate online learning with offline data.
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Collaborative Contextual Bayesian Optimization
CCBO enables collaborative contextual Bayesian optimization across clients with sublinear regret guarantees and shows substantial gains over non-collaborative methods in simulations and a hot rolling application even under heterogeneity.