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.
arXiv preprint arXiv:2110.01602 , year=
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Lloyd's algorithm on perturbed sub-Gaussian mixture samples has exponentially bounded mis-clustering rate after O(log n) iterations when initialized properly and perturbation is small relative to noise.
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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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Consistency of Lloyd's Algorithm Under Perturbations
Lloyd's algorithm on perturbed sub-Gaussian mixture samples has exponentially bounded mis-clustering rate after O(log n) iterations when initialized properly and perturbation is small relative to noise.