Frank-Wolfe and friends: a journey into projection-free first-order optimization methods
Optimization and Control
2021-06-21 v1
Abstract
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.
Keywords
Cite
@article{arxiv.2106.10261,
title = {Frank-Wolfe and friends: a journey into projection-free first-order optimization methods},
author = {Immanuel. M. Bomze and Francesco Rinaldi and Damiano Zeffiro},
journal= {arXiv preprint arXiv:2106.10261},
year = {2021}
}