Dr Estelle Massart
PhD in Mathematical Engineering - UCLouvain, Belgium
Research groups
Address
Mathematical Institute
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
Teaching
Lecturer for Prelims Computational Mathematics, MT 2020 and HT 2021.
Research interests
-
Optimization.
- Neural networks (optimization and generalization properties)
-
Data fitting on matrix manifolds - Riemannian optimization
-
Applications of Riemannian geometry (biomedical signals, model order reduction, wind field modeling).
Prizes, awards, and scholarships
Householder award, 2020.
Best Junior Presentation Award, Benelux meeting on Systems and Control, 2016
Major / recent publications
Preprints:
- C. Cartis, E. Massart, A. Otemissov,
Global optimization using random embeddings
2021. - C. Cartis, E. Massart, A. Otemissov,
Constrained global optimization of functions with low effective dimensionality using multiple random embeddings
2020.
Journal papers:
- A. Musolas, E. Massart, J. M. Hendrickx, P.-A. Absil, Y. Marzouk,
Low-rank multi-parametric covariance estimation, accepted to BIT Numerical Mathematics, 2021. - N.T. Son, P.-Y. Gousenbourger, E. Massart, and T. Stykel,
Balanced truncation for parametric linear systems using interpolation of Gramians: a comparison of algebraic and geometric approaches,
Special issue on model reduction of complex dynamical systems, to appear in the Springer International Series of Numerical Mathematics, 2020. - E. Massart, P.-A. Absil,
Quotient geometry with simple geodesics for the manifold of fixed-rank positive-semidefinite matrices,
SIAM Journal on Matrix Analysis and Applications 41(1), pp. 171-198, 2020.
Code available in the Manopt toolbox - P.-Y. Gousenbourger, E. Massart, P.-A. Absil,
Data fitting on manifolds with composite Bézier-like curves and blended cubic splines,
Journal of Mathematical Imaging and Vision, 61(5), pp. 645-671, 2019. - E. M. Massart, J. M. Hendrickx, P-A. Absil,
Matrix geometric means based on shuffled inductive sequences,
Linear Algebra and its Applications, 252, pp. 334-359, 2018. [Code]
Conference papers:
- E. Massart, V. Abrol,
Coordinate descent on the orthogonal group for recurrent neural network training,
Accepted to AAAI 2022. - C. Cartis, E. Massart, A. Otemissov,
Dimensionality reduction techniques for global optimization of functions with low effective dimensionality,
ICML workshop “Beyond first order methods in ML systems”. - For conference papers published before my arrival at the University of Oxford, please see my personal website.