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20182026
most citedA Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem

6 citations · 8 across the 4 of their papers we have counts for

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Showing 2026 · cs.LGShow all

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cs.LG2026

Instance-Adaptive Online Multiclass Multicalibration

Zhiming Huang, Jamie Morgenstern, Aaron Roth +1

We study online multiclass multicalibration over rounds, and give an algorithm with beyond-worst-case guarantees. With possible outcomes, forecasts lie in a simplex of dime…

cs.LG2026

Instance-Adaptive Online Multicalibration

Zhiming Huang, Jamie Morgenstern, Aaron Roth +1

We study online multicalibration beyond the worst-case. We give a single, efficient algorithm which dynamically interpolates between benign and worst-case sequences by adaptively r…