activity
20182020
most citedConstrained global optimization of functions with low effective dimensionality using multiple random embeddings

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

math.OC20203 cited

Constrained global optimization of functions with low effective dimensionality using multiple random embeddings

Coralia Cartis, Estelle Massart, Adilet Otemissov

We consider the bound-constrained global optimization of functions with low effective dimensionality, that are constant along an (unknown) linear subspace and only vary over the ef…

stat.CO2020

Low-rank multi-parametric covariance identification

Antoni Musolas, Estelle Massart, Julien M. Hendrickx +2

We propose a differential geometric construction for families of low-rank covariance matrices, via interpolation on low-rank matrix manifolds. In contrast with standard parametric…

math.NA2020

Balanced truncation for parametric linear systems using interpolation of Gramians: a comparison of algebraic and geometric approaches

Nguyen Thanh Son, Pierre-Yves Gousenbourger, Estelle Massart +1

When balanced truncation is used for model order reduction, one has to solve a pair of Lyapunov equations for two Gramians and uses them to construct a reduced-order model. Althoug…

cs.CV2019

Fitting, Comparison, and Alignment of Trajectories on Positive Semi-Definite Matrices with Application to Action Recognition

Benjamin Szczapa, Mohamed Daoudi, Stefano Berretti +3

In this paper, we tackle the problem of action recognition using body skeletons extracted from video sequences. Our approach lies in the continuity of recent works representing vid…

cs.IT2018

Blended smoothing splines on Riemannian manifolds

Pierre-Yves Gousenbourger, Estelle Massart, P. -A. Absil

We present a method to compute a fitting curve B to a set of data points d0,...,dm lying on a manifold M. That curve is obtained by blending together Euclidean Bézier curves obtain…