Search Results - "Vaisbourd, Yakov"

An elementary approach to tight worst case complexity analysis of gradient based methods by Teboulle, Marc, Vaisbourd, Yakov

“…This work presents a novel analysis that allows to achieve tight complexity bounds of gradient-based methods for convex optimization. We start by identifying…”
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The Sparse Principal Component Analysis Problem: Optimality Conditions and Algorithms by Beck, Amir, Vaisbourd, Yakov

“…Sparse principal component analysis addresses the problem of finding a linear combination of the variables in a given dataset with a sparse coefficients vector…”
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Rate of convergence analysis of dual-based variables decomposition methods for strongly convex problems by Beck, Amir, Tetruashvili, Luba, Vaisbourd, Yakov, Shemtov, Ariel

“…We consider the problem of minimizing the sum of a strongly convex function and a term comprising the sum of extended real-valued proper closed convex…”
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Maximum Entropy on the Mean and the Cram\'er Rate Function in Statistical Estimation and Inverse Problems: Properties, Models, and Algorithms by Vaisbourd, Yakov, Choksi, Rustum, Goodwin, Ariel, Hoheisel, Tim, Schönlieb, Carola-Bibiane

“…We explore a method of statistical estimation called Maximum Entropy on the Mean (MEM) which is based on an information-driven criterion that quantifies the…”
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The Sparse Principal Component Analysis Problem: Optimality Conditions and Algorithms by Beck, Amir, Vaisbourd, Yakov

“…Sparse principal component analysis addresses the problem of finding a linear combination of the variables in a given data set with a sparse coefficients…”
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First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems by Bolte, Jérôme, Sabach, Shoham, Teboulle, Marc, Vaisbourd, Yakov

“…We focus on nonconvex and nonsmooth minimization problems with a composite objective, where the differentiable part of the objective is freed from the usual…”
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