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SIAM Chapter Seminar
Daniel Rodriguez Carnegie Melllon University Title: FrankWolf with Away Steps Abstract: The FrankWolfe Algorithm for minimizing a convex function over a polytope has attractive properties due to its simplicity and low computational cost. We show that for some convex functions a variant of the FrankWolfe Algorithm, which performs "away steps" at certain iterations, generates a sequence of points whose objective values converge linearly to the minimum. We provide some insightful connections between the algorithm's rate of convergence and the geometry of the problem. Date: Tuesday, April 14, 2015 Time: 5:30 pm Location: Wean Hall 8220 