Clément Royer

Clement Royer
Develop optimization algorithms for problems arising in complex systems and data science.

Years at WID

2016 - present

About

Clément Royer was born and raised in Béarn, a tiny historical region of Southwestern France. He left the sight of the Pyrénées mountains to study in Bordeaux and Toulouse, where he also perfected his skills as an amateur musician. After completing his thesis in 2016, he came to Madison without much more than his manuscript and his clarinet.

Education

  • Engineering Degree, Computer Science and Applied Mathematics, ENSEEIHT, University of Toulouse, France
  • Ms.C., Computer Science, INPT, University of Toulouse, France.
  • Ph.D., Applied Mathematics, UT3 Paul Sabatier, University of Toulouse, France

Research Description

Clément Royer’s research interests revolve around numerical continuous optimization and all its applications. His current research focuses in particular on two aspects of the area: the introduction of randomness within otherwise deterministic optimization schemes and the worst-case complexity analysis of optimization algorithms. Following his Ph.D. work, he also maintains a high interest in derivative-free and simulation-based optimization.

Selected Publications

  • C. W. Royer, M. O'Neill and S. J. Wright. A Newton-CG algorithm with complexity guarantees for smooth unconstrained optimization. Mathematical Programming, 2019. DOI:10.1007/s10107-019-01362-7
  • S. Gratton, C. W. Royer and L. N. Vicente. A decoupled first/second-order steps technique for nonconvex nonlinear unconstrained optimization with improved complexity bounds. Mathematical Programming, 2018. DOI:10.1007/s10107-018-1328-7
  • C. W. Royer and S. J. Wright. Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM Journal on Optimization, 28(2):1448-1477, 2018.
  • S. Gratton, C. W. Royer, L. N. Vicente and Z. Zhang. Complexity and global rates of trust-region methods based on probabilistic models. IMA Journal on Numerical Analysis, 38(3):1579-1597, 2018.
  • S. Gratton, C. W. Royer, L. N. Vicente and Z. Zhang. Direct search based on probabilistic descent. SIAM Journal on Optimization, 25(3):1515-1541, 2015.