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arXiv · 1307.0873

New Analysis and Results for the Frank-Wolfe Method

Robert M. Freund·Paul Grigas
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Abstract

We present new results for the Frank-Wolfe method (also known as the conditional gradient method). We derive computational guarantees for arbitrary step-size sequences, which are then applied to various step-size rules, including simple averaging and constant step-sizes. We also develop step-size rules and computational guarantees that depend naturally on the warm-start quality of the initial (and subsequent) iterates. Our results include computational guarantees for both duality/bound gaps and the so-called FW gaps. Lastly, we present complexity bounds in the presence of approximate computation of gradients and/or linear optimization subproblem solutions.

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Robert M. Freund, Paul Grigas. 2014-06-02. New Analysis and Results for the Frank-Wolfe Method. https://arxiv.org/abs/1307.0873

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