Curriculum vitae

Royer Clément W.

Maître de conférences
LAMSADE

clement.royerping@lamsade.dauphinepong.fr
Bureau : P633
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Biographie

Clément W. Royer a obtenu son doctorat de l'université de Toulouse en mathématiques appliquées en 2016. Il est également ingénieur diplômé de l'ENSEEIHT (membre de l'Institut National Polytechnique de Toulouse), en informatique et mathématiques appliquées.

De 2016 à 2019, il était chercheur-postdoctorant au Wisconsin Institute for Discovery, laboratoire transdisciplinaire de l'université du Wisconsin-Madison, aux Etats-Unis. Il était alors membre du groupe d'optimisation ainsi que du pôle sciences des données.

Dernières publications

Articles

Bergou E., Diouane Y., Kungurtsev V., Royer C. (2022), A stochastic Levenberg-Marquardt method using random models with complexity results, SIAM/ASA Journal on Uncertainty Quantification, vol. 10, n°1, p. 507-536

Chan-Renous-Legoubin R., Royer C. (2022), A nonlinear conjugate gradient method with complexity guarantees and its application to nonconvex regression, EURO Journal on Computational Optimization, vol. 10, n°100044

Curtis F., Robinson D., Royer C., Wright S. (2021), Trust-Region Newton-CG with Strong Second-Order Complexity Guarantees for Nonconvex Optimization, SIAM Journal on Optimization, vol. 31, n°1, p. 518-544

Bergou E., Diouane Y., Kungurtsev V., Royer C. (2021), A Nonmonotone Matrix-Free Algorithm for Nonlinear Equality-Constrained Least-Squares Problems, SIAM Journal on Scientific Computing, vol. 43, n°5, p. S743-S766

Gratton S., Royer C., Vicente L. (2020), A decoupled first/second-order steps technique for nonconvex nonlinear unconstrained optimization with improved complexity bounds, 2199-1413, vol. 179, n°1-2, p. 195–222

Royer C., O’Neill M., Wright S. (2020), A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization, 2199-1413, vol. 180, n°1-2, p. 451–488

Gratton S., Royer C., Vicente L., Zhang Z. (2019), Direct search based on probabilistic feasible descent for bound and linearly constrained problems, Computational Optimization and Applications, vol. 72, n°3, p. 525-559

Gratton S., Royer C., Vicente L., Zhang Z. (2018), Complexity and global rates of trust-region methods based on probabilistic models, IMA Journal of Numerical Analysis, vol. 38, n°3, p. 1579-1597

Royer C., Wright S. (2018), Complexity Analysis of Second-Order Line-Search Algorithms for Smooth Nonconvex Optimization, SIAM Journal on Optimization, vol. 28, n°2, p. 1448-1477

Gratton S., Royer C., Vicente L. (2015), A second-order globally convergent direct-search method and its worst-case complexity, Optimization. A Journal of Mathematical Programming and Operations Research, vol. 65, n°6, p. 1105-1128

Gratton S., Royer C., Vicente L., Zhang Z. (2015), Direct Search Based on Probabilistic Descent, SIAM Journal on Optimization, vol. 25, n°3, p. 1515-1541

Chapitres d'ouvrage

Caillau J-B., Royer C. (2014), On the injectivity and nonfocal domains of the ellipsoid of revolution, in Gianna Stefani, Ugo Boscain, Jean-Paul Gauthier, Andrey Sarychev, Mario Sigalotti, Geometric Control Theory and Sub-Riemannian Geometry, Cortona: Springer, p. 73-85

Communications avec actes

Meunier L., Chevaleyre Y., Rapin J., Royer C., Teytaud O. (2020), On Averaging the Best Samples in Evolutionary Computation, in Thomas Bäck, Mike Preuss, André Deutz, Berlin Heidelberg, Springer, 661-674 p.

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