collaborators

8 papers

math.OC2026

A constructive approach to strengthen algebraic descriptions of function and operator classes

Anne Rubbens, Julien M. Hendrickx, Adrien Taylor

It is well known that functions (resp. operators) satisfying a property~ on a subset cannot necessarily be extended to a function (resp. operator) satisf…

math.OC2026

Identification of Nonlinear Acyclic Networks in Continuous Time from Nonzero Initial Conditions and Full Excitations

Ramachandran Anantharaman, Renato Vizuete, Julien M. Hendrickx +1

We propose a method to identify nonlinear acyclic networks in continuous time when the dynamics are located on the edges and all the nodes are excited. We show that it is necessary…

math.OC2026

Computer-aided analyses of stochastic first-order methods, via interpolation conditions for stochastic optimization

Anne Rubbens, Sébastien Colla, Julien M. Hendrickx

This work proposes a framework, embedded within the Performance Estimation framework (PEP), for obtaining worst-case performance guarantees on stochastic first-order methods. Given…

math.OC2025

On the Convex Interpolation for Linear Operators

Nizar Bousselmi, Zhicheng Deng, Jie Lu +2

The worst-case performance of an optimization method on a problem class can be analyzed using a finite description of the problem class, known as interpolation conditions. In this…

math.OC2025

A constraint-based approach to function interpolation, with application to performance estimation for weakly convex optimisation

Anne Rubbens, Julien M. Hendrickx

We consider the problem of obtaining interpolation constraints for function classes, i.e., necessary and sufficient constraints that a set of points, function values and (sub)gradi…

math.OC2025

Numerical Design of Optimized First-Order Algorithms

Yassine Kamri, Julien M. Hendrickx, François Glineur +1

We derive several numerical methods for designing optimized first-order algorithms in unconstrained convex optimization settings. Our methods are based on the Performance Estimatio…