Search Results for author: Ricardo Nanculef

Found 4 papers, 1 papers with code

Fast and Scalable Lasso via Stochastic Frank-Wolfe Methods with a Convergence Guarantee

1 code implementation24 Oct 2015 Emanuele Frandi, Ricardo Nanculef, Stefano Lodi, Claudio Sartori, Johan A. K. Suykens

Frank-Wolfe (FW) algorithms have been often proposed over the last few years as efficient solvers for a variety of optimization problems arising in the field of Machine Learning.

Complexity Issues and Randomization Strategies in Frank-Wolfe Algorithms for Machine Learning

no code implementations15 Oct 2014 Emanuele Frandi, Ricardo Nanculef, Johan Suykens

Frank-Wolfe algorithms for convex minimization have recently gained considerable attention from the Optimization and Machine Learning communities, as their properties make them a suitable choice in a variety of applications.

A Novel Frank-Wolfe Algorithm. Analysis and Applications to Large-Scale SVM Training

no code implementations3 Apr 2013 Hector Allende, Emanuele Frandi, Ricardo Nanculef, Claudio Sartori

In this paper, we present and analyze a novel variant of the FW method based on a new way to perform away steps, a classic strategy used to accelerate the convergence of the basic FW procedure.

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