Publications

Preprints

(2022) Computing second-order points under equality constraints: revisiting Fletcher’s augmented Lagrangian, F. Goyens, A. Eftekhari, N. Boumal. Arxiv
(2021) Nonlinear matrix recovery using optimization on the Grassmann manifold, F. Goyens, C. Cartis, A. Eftekhari. Arxiv

(2020) Smoothing of point clouds using Riemannian optimization, F. Goyens, S. Chretien, C. Cartis. ICML, Beyond first order methods in Machine Learning Workshop
(2019) Nonlinear matrix recovery, F. Goyens, A. Eftekhari, C. Cartis. NeurIPS, Beyond first order methods in Machine Learning Workshop
(2018) A Probabilistic Model for Precedence Rules and Reactionary Delay in Air Traffic Management, F. Goyens, F. Gonze, A. Simonetto, E. Huens, J. Boucquey, R. M. Jungers. ICRAT

ICML, poster as part of the workshop “Beyond first order methods in Machine Learning”, Online conference on July 17, 2020
Mathematics of Data Science, graduate online conference on June 11, 2020
Seminar at the Mathematical Engineering department in Louvain-la-Neuve (Belgium) on December 17, 2019
NeurIPS poster as part of the workshop “Beyond first order methods in Machine Learning”, Vancouver (Canada) on December 13, 2019
2nd IMA Conference On Inverse Problems From Theory To Application, London (UK) on September 5, 2020
ICCOPT, Berlin (Germany) on August 7, 2019
Applied Inverse Problems Conference, Grenoble (France) on July 12, 2019
Signal Processing with Adaptive Sparse Structured Representations (SPARS), Toulouse (France) on July 4, 2019
British Applied Mathematics Colloquium, University of Bath (UK), on April 26, 2019
3rd IMA Conference on the Mathematical Challenges of Big Data, London (UK) on December 10, 2018
Numerical Analysis group internal seminar, Oxford (UK) on November 13, 2018
ISMP, Bordeaux (France), July 2018
IMA Conference on Numerical Linear Algebra and Optimization, Birmingham (UK) on June 28, 2018

(PhD thesis, 2021) A Riemannian perspective on matrix recovery and constrained optimization
(Master thesis, 2016) Quasi-Newton methods for nonsmooth Riemannian optimization (Advisers: P.-A. Absil, W. Huang)