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cs.LG2026
Optimal Multiclass Online Regret with Arbitrary Label Spaces
Sajad Ashkezari, Shai Ben-David
We determine the optimal regret in agnostic multiclass online learning with arbitrary, possibly infinite, label spaces. For every hypothesis class of multiclass Littlestone dimensi…
cs.LG2026
Robust Online Learning
Sajad Ashkezari
We study the problem of learning robust classifiers where the classifier will receive a perturbed input. Unlike robust PAC learning studied in prior work, here the clean data and i…
cs.LG2026
Online Learning with Improving Agents: Multiclass, Budgeted Agents and Bandit Learners
Sajad Ashkezari, Shai Ben-David
We investigate the recently introduced model of learning with improvements, where agents are allowed to make small changes to their feature values to be warranted a more desirable…