5 citations · 11 across the 9 of their papers we have counts for
10 papers · 1 filter
Random sketching of operators with application to learning preconditioners
Oleg Balabanov, Anthony Nouy, Alexandre Pasco
We propose a new random sketching approach for embedding high-dimensional Hilbert-Schmidt operators, using random input-output pairs. Such operator can then be approximated in a lo…
Surrogate to Poincaré inequalities on manifolds for structured dimension reduction in nonlinear feature spaces
Alexandre Pasco, Anthony Nouy
This paper is concerned with the approximation of continuously differentiable functions with high-dimensional input by a composition of two functions: a feature map that extracts f…
Surrogate to Poincaré inequalities on manifolds for dimension reduction in nonlinear feature spaces
Anthony Nouy, Alexandre Pasco
We aim to approximate a continuously differentiable function by a composition of functions where $g:\mathbb{R}^d \rightarrow \mat…
Boosted optimal weighted least-squares
Cécile Haberstich, Anthony Nouy, Guillaume Perrin
This paper is concerned with the approximation of a function in a given approximation space of dimension from evaluations of the function at suitably chosen point…
Approximation and learning with compositional tensor trains
Martin Eigel, Charles Miranda, Anthony Nouy +1
We introduce compositional tensor trains (CTTs) for the approximation of multivariate functions, a class of models obtained by composing low-rank functions in the tensor-train form…
Optimal sampling for least squares approximation with general dictionaries
Philipp Trunschke, Anthony Nouy
We consider the problem of approximating an unknown function from point evaluations. This problem is a crucial subproblem in many modern (nonlinear) approximation schemes. When obt…