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FrankWolfe.jl: a high-performance and flexible toolbox for Frank-Wolfe algorithms and Conditional Gradients

  • We present FrankWolfe.jl, an open-source implementation of several popular Frank–Wolfe and conditional gradients variants for first-order constrained optimization. The package is designed with flexibility and high performance in mind, allowing for easy extension and relying on few assumptions regarding the user-provided functions. It supports Julia’s unique multiple dispatch feature, and it interfaces smoothly with generic linear optimization formulations using MathOptInterface.jl.
Author:Besançon Mathieu, Alejandro Carderera, Sebastian Pokutta
Document Type:Article
Parent Title (English):INFORMS Journal on Computing
First Page:2383
Last Page:2865
Year of first publication:2022
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