FrankWolfe.jl: A High-Performance and Flexible Toolbox for Frank–Wolfe Algorithms and Conditional Gradients
介绍了一个开源的Julia工具箱FrankWolfe.jl，实现了多种Frank–Wolfe和条件梯度算法，用于一阶约束优化，具有高灵活性和高性能，易于扩展并与通用线性优化接口兼容。
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.