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Email : clement.royer(at)
Clément Royer
Université Paris-Dauphine
Place du Maréchal de Lattre de Tassigny
75016 Paris
I am also on Google Scholar and Twitter.

Clément W. Royer

La version française de cette page se trouve ici.

My research essentially revolves around the field of numerical optimization and its applications, particularly in complex systems and data science.
My current work aims at developing efficient nonconvex optimization algorithms, with a focus on incorporating randomness (typically within linear algebra techniques), and establishing complexity guarantees for those frameworks.
Following the lines of my Ph.D., I also maintain a high interest in derivative-free optimization and its applications to solving simulation-based problems.

Submitted preprints

A subsampling line-search method with second-order results
     E. Bergou, Y. Diouane, V. Kungurstev and C. W. Royer.
     Technical report arXiv:1810.07211, 2018.
A stochastic Levenberg-Marquardt method using random models with application to data assimilation
     E. Bergou, Y. Diouane, V. Kungurstev and C. W. Royer.
     Technical report arXiv:1807.02176, 2018.

Articles in refereed journals

A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization
     C. W. Royer, M. O'Neill and S. J. Wright.
     Mathematical Programming, online since January 2019.
Direct search based on probabilistic feasible descent for bound and linearly constrained problems
     S. Gratton, C. W. Royer, L. N. Vicente and Z. Zhang.
     Computational Optimization and Applications, 72(3):525-559, 2019.
A decoupled first/second-order steps technique for nonconvex nonlinear unconstrained optimization with improved complexity bounds
     S. Gratton, C. W. Royer and L. N. Vicente.
     Mathematical Programming, online since September 2018.
Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization
     C. W. Royer and S. J. Wright.
     SIAM Journal on Optimization, 28(2):1448-1477, 2018.
Complexity and global rates of trust-region methods based on probabilistic models
     S. Gratton, C. W. Royer, L. N. Vicente and Z. Zhang.
     IMA Journal of Numerical Analysis, 38(3):1579-1597, 2018.
A second-order globally convergent direct-search method and its worst-case complexity
     S. Gratton, C. W. Royer and L. N. Vicente.
     Optimization, 65(6):1105-1128, 2016.
Direct search based on probabilistic descent
     S. Gratton, C. W. Royer, L. N. Vicente and Z. Zhang.
     SIAM Journal on Optimization, 25(3):1515-1541, 2015.

Conference proceedings

On the injectivity and nonfocal domains of the ellipsoid of revolution
     J.-B. Caillau and C. W. Royer.
     Geometric Control Theory and Sub-Riemannian Geometry, 73-86, Springer, 2014
     Proceedings of the INDAM meeting on Geometric Control and sub-Riemannian geometry, May 2012.

PhD Thesis

Derivative-Free Optimization Methods based on Probabilistic and Deterministic Properties: Complexity Analysis and Numerical Relevance.
     C. W. Royer, University of Toulouse, November 2016.
     Defence slides

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Co-author list (in reverse chronological order)

Vyacheslav Kungurstev
Youssef Diouane
El Houcine Bergou
Michael O'Neill
Stephen J. Wright
Zaikun Zhang
Luís Nunes Vicente
Serge Gratton
Jean-Baptiste Caillau

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This page was designed by Clothilde Royer, many thanks to her.
Materials on this page are available under Creative Commons CC BY-NC 4.0 license.