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cs.LG2026
Agnostic learning in (almost) optimal time via Gaussian surface area
Lucas Pesenti, Lucas Slot, Manuel Wiedmer
The complexity of learning a concept class under Gaussian marginals in the difficult agnostic model is closely related to its -approximability by low-degree polynomials. For a…
cs.LG2024
Testably Learning Polynomial Threshold Functions
Lucas Slot, Stefan Tiegel, Manuel Wiedmer
Rubinfeld & Vasilyan recently introduced the framework of testable learning as an extension of the classical agnostic model. It relaxes distributional assumptions which are difficu…