A robust variant of binary search achieves regret O(C + log T) for dynamic pricing with known corruption C and O(C + log² T) when unknown.
arXiv preprint arXiv:2206.07528 , year =
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Finite O(d log d) regret bounds for online inverse linear optimization under M-convex action sets, plus O((C+1)d log d) corruption-robust bounds without knowing C.
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Toward Optimal Regret in Robust Pricing: Decoupling Corruption and Time
A robust variant of binary search achieves regret O(C + log T) for dynamic pricing with known corruption C and O(C + log² T) when unknown.
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Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets
Finite O(d log d) regret bounds for online inverse linear optimization under M-convex action sets, plus O((C+1)d log d) corruption-robust bounds without knowing C.