3 papers
math.ST2022
Pattern recovery by SLOPE
Małgorzata Bogdan, Xavier Dupuis, Piotr Graczyk +4
SLOPE is a popular method for dimensionality reduction in the high-dimensional regression. Indeed some regression coefficient estimates of SLOPE can be null (sparsity) or can be eq…
math.NA2021
A semi-Lagrangian scheme for Hamilton-Jacobi-Bellman equations with oblique boundary conditions
Elisa Calzola, Elisabetta Carlini, Xavier Dupuis +1
We investigate in this work a fully-discrete semi-Lagrangian approximation of second order possibly degenerate Hamilton-Jacobi-Bellman (HJB) equations on a bounded domain with obli…
math.OC2019
The Geometry of Sparse Analysis Regularization
Xavier Dupuis, Samuel Vaiter
Analysis sparsity is a common prior in inverse problem or machine learning including special cases such as Total Variation regularization, Edge Lasso and Fused Lasso. We study the…