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• W2949161035 abstract "We consider problem of minimizing a function, which is sum of a linear function and a composition of a strongly convex function with a linear transformation, over a compact polyhedral set. Jaggi and Lacoste-Julien [14] showed that conditional gradient method with away steps employed on aforementioned problem without additional linear term has linear rate of convergence, depending on so-called pyramidal width of feasible set. We revisit this result and provide a variant of algorithm and an analysis that is based on simple duality arguments, as well as corresponding error bounds. This new analysis (a) enables incorporation of additional linear term, (b) does not require a linear-oracle that outputs an extreme point of linear mapping of feasible set and (c) depends on a new termed the vertex-facet distance constant, which is explicitly expressed in terms of problem's parameters and geometry of feasible set. This constant replaces pyramidal width, which is difficult to evaluate." @default.
• W2949161035 created "2019-06-27" @default.
• W2949161035 creator A5019451567 @default.
• W2949161035 creator A5069363394 @default.
• W2949161035 date "2015-04-20" @default.
• W2949161035 modified "2023-09-27" @default.
• W2949161035 title "Linearly Convergent Away-Step Conditional Gradient for Non-strongly Convex Functions" @default.
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• W2949161035 hasPublicationYear "2015" @default.
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