Stochastic Frank-Wolfe Methods for Nonconvex OptimizationEI

    Cited by: 21|Bibtex|21|

    Allerton, pp. 1244-1251, 2016.

    Abstract:

    We study Frank-Wolfe methods for nonconvex stochastic and finite-sum optimization problems. Frank-Wolfe methods (in the convex case) have gained tremendous recent interest in machine learning and optimization due to their projection-free property and their ability to exploit structured constraints. However, our understanding of these algo...More
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