Frank–Wolfe and friends: a journey into projection-free first-order optimization methods
这篇综述回顾了Frank–Wolfe方法在数据科学等领域的复兴，介绍了其原理、变体及在多种场景下的应用，适合对优化算法感兴趣的读者。
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.