Randomized algorithms have proven to perform well on a large class of numerical linear algebra problems. Their theoretical analysis is critical to provide gu...

Les méthodes de lagrangien augmenté (AL) forment une classe bien connue d’algorithmes pour les problèmes d’optimisation sous contraintes. Elles ont été é...

Cellular solids are structures which have applications in mechanical engineering to make lightweight structures and heat exchangers, in biomedical engineer...

Nous présentons une analyse de la borne de complexité dans le pire des cas pour les méthodes de région de confiance en présence d'approximations du Hessien...

The purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...

We develop a trust-region method for minimizing the sum of a smooth term \(f\) and a nonsmooth term \(h\), both of which can be nonconvex. Each iteratio...

Nous développons une méthode de points intérieurs pour l'optimisation non lisse régularisée avec contraintes de bornes. Notre méthode résout de manière ité...

The fine-tuning of Large Language Models (LLMs) has enabled them to recently achieve milestones in natural language processing applications. The emergenc...

The cosine measure was introduced in 2003 to quantify the richness of a finite positive spanning sets of directions in the context of derivative-free direc...

A challenge in aircraft design optimization is the presence of non-computable, so-called hidden, constraints that do not return a value in certain regions of...

In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...

Cet article propose une nouvelle étape à ajouter à chaque itération de la Méthode de Recherche Directe Direct Search Method (DSM) en anglais) pour renfor...

In this work, we propose a non-intrusive and training free method to detect behind-the-meter (BTM) electric vehicle (EV) charging events from the data measur...

La bibliothèque de sous-programmes Harwell (HSL) est une suite renommée de méthodes numériques efficaces et robustes conçus pour résoudre des problèmes mathé...

Monte Carlo (MC) is widely used for the simulation of discrete time Markov chains. We consider the case of a \(d\)-dimensional continuous state space and w...

This work introduces a novel multi-fidelity blackbox optimization algorithm designed to alleviate the resource-intensive task of evaluating infeasible points...

We consider the set of graphs that can be constructed from a one-vertex graph by repeatedly adding a clique or a stable set linked to all or none of the vert...

L'apprentissage par renforcement (RL) pour les processus décisionnels de Markov partiellement observables (POMDP) est un problème difficile car les décisions...

This paper first introduces a computationally efficient approach for conducting a time-series impact analysis of electric vehicle (EV) charging on the loadin...

This paper addresses risk averse constrained optimization problems where the objective and constraint functions can only be computed by a blackbox subject to...