11 citations · 35 across the 15 of their papers we have counts for
16 papers · 1 filter
Beyond Short Steps in Frank-Wolfe Algorithms
David Martínez-Rubio, Sebastian Pokutta
We introduce novel techniques to enhance Frank-Wolfe algorithms by leveraging function smoothness beyond traditional short steps. Our study focuses on Frank-Wolfe algorithms with s…
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martínez-Rubio, Sebastian Pokutta
We introduce a Riemannian optimistic online learning algorithm for Hadamard manifolds based on inexact implicit updates. Unlike prior work, our method can handle in-manifold constr…
State-of-the-art Methods for Pseudo-Boolean Solving with SCIP
Gioni Mexi, Dominik Kamp, Yuji Shinano +8
The Pseudo-Boolean problem deals with linear or polynomial constraints with integer coefficients over Boolean variables. The objective lies in optimizing a linear objective functio…
An Algorithm-Independent Measure of Progress for Linear Constraint Propagation
Boro Sofranac, Ambros Gleixner, Sebastian Pokutta
Propagation of linear constraints has become a crucial sub-routine in modern Mixed-Integer Programming (MIP) solvers. In practice, iterative algorithms with tolerance-based stoppin…
FrankWolfe.jl: a high-performance and flexible toolbox for Frank-Wolfe algorithms and Conditional Gradients
Mathieu Besançon, Alejandro Carderera, Sebastian Pokutta
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 d…
Local and Global Uniform Convexity Conditions
Thomas Kerdreux, Alexandre d'Aspremont, Sebastian Pokutta
We review various characterizations of uniform convexity and smoothness on norm balls in finite-dimensional spaces and connect results stemming from the geometry of Banach spaces w…