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clement.royer@lamsade.dauphine.fr
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: P633
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Clément W. Royer got his PhD in applied mathematics from the university of Toulouse in 2016. He also holds an engineer degree in computer science and applied mathematics from the grande école ENSEEIHT (member of the National Polytechnique Institute of Toulouse).
From 2016 to 2019, he was a postdoctoral researcher at the Wisconsin Institute for Discovery, a transdisciplinary laboratory at the University of Wisconsin-Madison (USA). He was then a member of the optimization group and the data science hub.
Hare W., Jarry-Bolduc G., Kerleau S., Royer C. (2024), Using orthogonally structured positive bases for constructing positive k-spanning sets with cosine measure guarantees, Linear Algebra and its Applications, vol. 680, p. 183-207 
Roberts L., Royer C. (2023), Direct Search Based on Probabilistic Descent in Reduced Spaces, SIAM Journal on Optimization, vol. 33, n°4, p. 3057-3082
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, p. 100044
Bergou E., Diouane Y., Kunc V., Kungurtsev V., Royer C. (2022), A Subsampling Line-Search Method with Second-Order Results, INFORMS Journal on Optimization, vol. 4, n°4, p. 347-445
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
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
Royer C., O’Neill M., Wright S. (2020), A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization, Mathematical Programming, vol. 180, n°1-2, p. 451–488
Gratton S., Royer C., Vicente L. (2020), A decoupled first/second-order steps technique for nonconvex nonlinear unconstrained optimization with improved complexity bounds, Mathematical Programming, vol. 179, n°1-2, p. 195–222
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., Zhang Z. (2015), Direct Search Based on Probabilistic Descent, SIAM Journal on Optimization, vol. 25, n°3, p. 1515-1541
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
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
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.
Goyens F., Royer C. (2024), Riemannian trust-region methods for strict saddle functions with complexity guarantees, Paris, Preprint Lamsade, 1-36 p.
