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Frank–Wolfe algorithm

Known as: Conditional gradient method, Frank-Wolfe, Frank-Wolfe algorithm 
The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional… 
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Related topics

Related topics

18 relations
Active set methodAlgorithmConstrained optimizationConvex function

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2019
Highly Cited
2019
One Sample Stochastic Frank-Wolfe
One of the beauties of the projected gradient descent method lies in its rather simple mechanism and yet stable behavior with… 
Highly Cited
2018
Highly Cited
2018
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks
Depending on how much information an adversary can access to, adversarial attacks can be classified as white-box attack and black… 
2018
2018
Deep Frank-Wolfe For Neural Network Optimization
Learning a deep neural network requires solving a challenging optimization problem: it is a high-dimensional, non-convex and non… 
2017
2017
Linear Convergence of a Frank-Wolfe Type Algorithm over Trace-Norm Balls
We propose a rank-$k$ variant of the classical Frank-Wolfe algorithm to solve convex optimization over a trace-norm ball. Our… 
Highly Cited
2016
Highly Cited
2016
Stochastic Frank-Wolfe methods for nonconvex optimization
We study Frank-Wolfe methods for nonconvex stochastic and finite-sum optimization problems. Frank-Wolfe methods (in the convex… 
Highly Cited
2014
Highly Cited
2014
Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets
The Frank-Wolfe method (a.k.a. conditional gradient algorithm) for smooth optimization has regained much interest in recent years… 
2014
2014
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms
We study parallel and distributed Frank-Wolfe algorithms; the former on shared memory machines with mini-batching, and the latter… 
Highly Cited
2013
Highly Cited
2013
The Stiff Is Moving - Conjugate Direction Frank-Wolfe Methods with Applications to Traffic Assignment
We present versions of the Frank-Wolfe method for linearly constrained convex programs, in which consecutive search directions… 
Highly Cited
2009
Highly Cited
2009
A generalized conditional gradient method and its connection to an iterative shrinkage method
Abstract This article combines techniques from two fields of applied mathematics: optimization theory and inverse problems. We… 
Highly Cited
1985
Highly Cited
1985
Improved Efficiency of the Frank-Wolfe Algorithm for Convex Network Programs
We discuss methods for speeding up convergence of the Frank-Wolfe algorithm for solving nonlinear convex programs. Models… 
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