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cs.DS2026
Robust Learning with Optimal Error
Guy Blanc
We construct algorithms with optimal error for learning with adversarial noise. The overarching theme of this work is that the use of \textsl{randomized} hypotheses can substantial…
cs.DS2025
Differential privacy from axioms
Guy Blanc, William Pires, Toniann Pitassi
Differential privacy (DP) is the de facto notion of privacy both in theory and in practice. However, despite its popularity, DP imposes strict requirements which guard against stro…
cs.DS2025
Instance-Optimal Uniformity Testing and Tracking
Guy Blanc, Clément L. Canonne, Erik Waingarten
In the uniformity testing task, an algorithm is provided with samples from an unknown probability distribution over a (known) finite domain, and must decide whether it is the unifo…