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cs.LG2026
Efficiently Learning Drifting Halfspaces with Massart Noise
Mingchen Ma, Guyang Cao, Jelena Diakonikolas +1
We study the problem of learning a drifting concept in the presence of Massart noise. In this framework, an online learner has access to a history of independent samples whose labe…
cs.LG2026
Polynomial-Time Robust Multiclass Linear Classification under Gaussian Marginals
Ilias Diakonikolas, Giannis Iakovidis, Mingchen Ma
We study the task of agnostic learning of multiclass linear classifiers under the Gaussian distribution. Given labeled examples from a distribution over $\mathbb{R}^d \tim…
cs.LG2022
Clustering with Queries under Semi-Random Noise
Alberto Del Pia, Mingchen Ma, Christos Tzamos
The seminal paper by Mazumdar and Saha \cite{MS17a} introduced an extensive line of work on clustering with noisy queries. Yet, despite significant progress on the problem, the pro…