5 papers
On the Slow Convergence to Trivial Solutions of Algorithms for Hard Optimization Problems
Ali Hussaini Umar, Jean Barbier, Matthieu Jonckheere +1
Hard combinatorial optimization problems, many of which are NP-hard, present fundamental algorithmic challenges. Average-case analysis on random instances has emerged as a powerful…
Online Matching via Reinforcement Learning: An Expert Policy Orchestration Strategy
Chiara Mignacco, Matthieu Jonckheere, Gilles Stoltz
Online matching problems arise in many complex systems, from cloud services and online marketplaces to organ exchange networks, where timely, principled decisions are critical for…
Queuing dynamics of asynchronous Federated Learning
Louis Leconte, Matthieu Jonckheere, Sergey Samsonov +1
We study asynchronous federated learning mechanisms with nodes having potentially different computational speeds. In such an environment, each node is allowed to work on models wit…
FEMDA: a unified framework for discriminant analysis
Pierre Houdouin, Matthieu Jonckheere, Frederic Pascal
Although linear and quadratic discriminant analysis are widely recognized classical methods, they can encounter significant challenges when dealing with non-Gaussian distributions…
Policy Optimization via Adv2: Adversarial Learning on Advantage Functions
Matthieu Jonckheere, Chiara Mignacco, Gilles Stoltz
We revisit the reduction of learning in adversarial Markov decision processes [MDPs] to adversarial learning based on --values; this reduction has been considered in a number of…