2 citations · 6 across the 9 of their papers we have counts for
10 papers
Discrete eigenvalue optimization from entropic smoothing and first-order methods
Deborah Hendrych, Mathieu Besançon, Sebastian Pokutta
We study the maximization of the minimum eigenvalue under combinatorial and integrality constraints. We propose a new approach based on branch-and-bound combines entropic smoothing…
Graph Isomorphism: Mixed-Integer Convex Optimization from First-Order Methods
Wenjie Xiao, Mathieu Besançon, Patrick Gelß +3
The graph isomorphism (GI) problem, which asks whether two graphs are structurally identical, occupies a unique position in computational complexity -- it is neither known to be so…
SparseSwaps: Tractable LLM Pruning Mask Refinement at Scale
Max Zimmer, Christophe Roux, Moritz Wagner +2
The resource requirements of neural networks can be significantly reduced through pruning - the removal of seemingly less important parameters. However, for LLMs, full retraining t…
Boscia.jl: A review and tutorial
Wenjie Xiao, Deborah Hendrych, Mathieu Besançon +1
Mixed-integer nonlinear optimization (MINLP) comprises a large class of problems that are challenging to solve and exhibit a wide range of structures. The Boscia framework (Hendryc…
A Frank-Wolfe-based primal heuristic for quadratic mixed-integer optimization
Gioni Mexi, Deborah Hendrych, Sébastien Designolle +2
We propose a primal heuristic for quadratic mixed-integer problems. Our method extends the Boscia framework -- originally a mixed-integer convex solver leveraging a Frank-Wolfe-bas…
Secant Line Search for Frank-Wolfe Algorithms
Deborah Hendrych, Mathieu Besançon, David Martínez-Rubio +1
We present a new step-size strategy based on the secant method for Frank-Wolfe algorithms. This strategy, which requires mild assumptions about the function under consideration, ca…
Improved algorithms and novel applications of the FrankWolfe.jl library
Mathieu Besançon, Sébastien Designolle, Jannis Halbey +6
Frank-Wolfe (FW) algorithms have emerged as an essential class of methods for constrained optimization, especially on large-scale problems. In this paper, we summarize the algorith…
Network Design for the Traffic Assignment Problem with Mixed-Integer Frank-Wolfe
Kartikey Sharma, Deborah Hendrych, Mathieu Besançon +1
We tackle the network design problem for centralized traffic assignment, which can be cast as a mixed-integer convex optimization (MICO) problem. For this task, we propose differen…
Solving the Optimal Experiment Design Problem with Mixed-Integer Convex Methods
Deborah Hendrych, Mathieu Besançon, Sebastian Pokutta
We tackle the Optimal Experiment Design Problem, which consists of choosing experiments to run or observations to select from a finite set to estimate the parameters of a system. T…
Convex mixed-integer optimization with Frank-Wolfe methods
Deborah Hendrych, Hannah Troppens, Mathieu Besançon +1
Mixed-integer nonlinear optimization encompasses a broad class of problems that present both theoretical and computational challenges. We propose a new type of method to solve thes…