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
Conference papers
- (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
Talks
- 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
Thesis
- (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)