40 citations · 153 across the 24 of their papers we have counts for
6 papers · 1 filter
Flexible block-iterative analysis for the Frank-Wolfe algorithm
Gábor Braun, Jannis Halbey, Sebastian Pokutta +1
We prove that the block-coordinate Frank-Wolfe (BCFW) algorithm converges with state-of-the-art rates in both convex and nonconvex settings under a very mild "block-iterative" assu…
Alternating Linear Minimization: Revisiting von Neumann's alternating projections
Gábor Braun, Sebastian Pokutta, Robert Weismantel
In 1933 von Neumann proved a beautiful result that one can approximate a point in the intersection of two convex sets by alternating projections, i.e., successively projecting on o…
Conditional Gradient Methods
Gábor Braun, Alejandro Carderera, Cyrille W. Combettes +4
The purpose of this survey is to serve both as a gentle introduction and a coherent overview of state-of-the-art Frank--Wolfe algorithms, also called conditional gradient algorithm…
Dual Prices for Frank--Wolfe Algorithms
Gábor Braun, Sebastian Pokutta
In this note we observe that for constrained convex minimization problems over a polytope , dual prices for the linear program $\min_{z \in P} \nabla f(x) z…
Blended Conditional Gradients: the unconditioning of conditional gradients
Gábor Braun, Sebastian Pokutta, Dan Tu +1
We present a blended conditional gradient approach for minimizing a smooth convex function over a polytope P, combining the Frank--Wolfe algorithm (also called conditional gradient…
Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory
Gábor Braun, Cristóbal Guzmán, Sebastian Pokutta
We present an information-theoretic approach to lower bound the oracle complexity of nonsmooth black box convex optimization, unifying previous lower bounding techniques by identif…