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- W2247185167 abstract "We present new results for the conditional gradient method (also known as the Frank-Wolfe 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 Wolfe gaps. Lastly, we present complexity bounds in the presence of approximate computation of gradients and/or linear optimization subproblem solutions." @default.
- W2247185167 created "2016-06-24" @default.
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- W2247185167 date "2013-07-10" @default.
- W2247185167 modified "2023-09-25" @default.
- W2247185167 title "New Analysis and Results for the Conditional Gradient Method" @default.
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