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Creators/Authors contains: "Kur, Gil"

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  1. ; ; (, Proceedings of Thirty Third Conference on Learning Theory, PMLR)
    Abernethy, Jacob; Agarwal, Shivani (Ed.)
    We develop a technique for establishing lower bounds on the sample complexity of Least Squares (or, Empirical Risk Minimization) for large classes of functions. As an application, we settle an open problem regarding optimality of Least Squares in estimating a convex set from noisy support function measurements in dimension d \geq 6. Specifically, we establish that Least Squares is mimi- max sub-optimal, and achieves a rate of n^{-2/(d-1)} whereas the minimax rate is n^{-4/(d+3)}. 
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    Accepted Manuscript Full Text Available
  2. ; ; (, Conference on Learning Theory)
    Accepted Manuscript Full Text Available