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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3 Pith papers cite this work. Polarity classification is still indexing.
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A stagewise greedy algorithm for semiparametric contextual dynamic pricing achieves regret T to the max of 1/2 and 3 over (2 beta plus 1) for linear m, with a matching lower bound proving optimality.
Nearest-neighbour matching achieves usual convergence rates under general transferability conditions on source-target distribution pairs, relaxing compact support and bounded density assumptions.
citing papers explorer
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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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Optimal Semiparametric Dynamic Pricing with Feature Diversity
A stagewise greedy algorithm for semiparametric contextual dynamic pricing achieves regret T to the max of 1/2 and 3 over (2 beta plus 1) for linear m, with a matching lower bound proving optimality.
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Nearest-Neighbour Matching on Unbounded Supports and Covariate Shift Transfer
Nearest-neighbour matching achieves usual convergence rates under general transferability conditions on source-target distribution pairs, relaxing compact support and bounded density assumptions.