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FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank–Wolfe Algorithms and Conditional Gradients

Author

Listed:
  • Mathieu Besançon

    (Zuse Institute Berlin, 14195 Berlin, Germany)

  • Alejandro Carderera

    (Zuse Institute Berlin, 14195 Berlin, Germany; Georgia Institute of Technology, Atlanta, Georgia 30308)

  • Sebastian Pokutta

    (Zuse Institute Berlin, 14195 Berlin, Germany; Technische Universität Berlin, 10623 Berlin, Germany)

Abstract

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 .

Suggested Citation

  • Mathieu Besançon & Alejandro Carderera & Sebastian Pokutta, 2022. "FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank–Wolfe Algorithms and Conditional Gradients," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2611-2620, September.
    • Handle: RePEc:inm:orijoc:v:34:y:2022:i:5:p:2611-2620
    DOI: 10.1287/ijoc.2022.1191
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    References listed on IDEAS

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    1. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
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