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Frank-Wolfe and friends: a journey into projection-free first-order optimization methods

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arxiv 2106.10261 v1 pith:PNN7ALAY submitted 2021-06-18 math.OC

Immanuel. M. Bomze , Francesco Rinaldi , Damiano Zeffiro This is my paper · ORCID
classification math.OC
keywords first-orderoptimizationfrank-wolfemethodsaccountapplicabilityapplicationapproach
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Invented some 65 years ago in a seminal paper by Marguerite Straus-Frank and Philip Wolfe, the Frank-Wolfe method recently enjoys a remarkable revival, fuelled by the need of fast and reliable first-order optimization methods in Data Science and other relevant application areas. This review tries to explain the success of this approach by illustrating versatility and applicability in a wide range of contexts, combined with an account on recent progress in variants, both improving on the speed and efficiency of this surprisingly simple principle of first-order optimization.

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