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- W2076095618 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." @default.
- W2076095618 created "2016-06-24" @default.
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- W2076095618 date "2014-11-28" @default.
- W2076095618 modified "2023-09-26" @default.
- W2076095618 title "New analysis and results for the Frank–Wolfe method" @default.
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- W2076095618 doi "https://doi.org/10.1007/s10107-014-0841-6" @default.
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