78 citations · 335 across the 44 of their papers we have counts for
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Learning sparse mixtures of rankings from noisy information
Anindya De, Ryan O'Donnell, Rocco Servedio
We study the problem of learning an unknown mixture of rankings over elements, given access to noisy samples drawn from the unknown mixture. We consider a range of differen…
Hardness Results for Agnostically Learning Low-Degree Polynomial Threshold Functions
Ilias Diakonikolas, Ryan O'Donnell, Rocco A. Servedio +1
Hardness results for maximum agreement problems have close connections to hardness results for proper learning in computational learning theory. In this paper we prove two hardness…
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Jon Feldman, Ryan O'Donnell, Rocco A. Servedio
We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kearns et al.…