102 citations · 164 across the 17 of their papers we have counts for
26 papers
Worst-Case Completion of Tensors with Approximately Few ANOVA Terms
Simon Foucart, Jingchun Shao
In this article, the problem of completing a tensor from some incomplete knowledge of its entries is treated by adopting a worst-case perspective, given the realistic assumption th…
S-Procedure Relaxation: a Case of Exactness Involving Chebyshev Centers
Simon Foucart, Chunyang Liao
Optimal recovery is a mathematical framework for learning functions from observational data by adopting a worst-case perspective tied to model assumptions on the functions to be le…
On the Optimal Recovery of Graph Signals
Simon Foucart, Chunyang Liao, Nate Veldt
Learning a smooth graph signal from partially observed data is a well-studied task in graph-based machine learning. We consider this task from the perspective of optimal recovery,…
Near-Optimal Estimation of Linear Functionals with Log-Concave Observation Errors
Simon Foucart, Grigoris Paouris
This note addresses the question of optimally estimating a linear functional of an object acquired through linear observations corrupted by random noise, where optimality pertains…
The Sparsity of LASSO-type Minimizers
Simon Foucart
This note extends an attribute of the LASSO procedure to a whole class of related procedures, including square-root LASSO, square LASSO, LAD-LASSO, and an instance of generalized L…
Full Recovery from Point Values: an Optimal Algorithm for Chebyshev Approximability Prior
Simon Foucart
Given pointwise samples of an unknown function belonging to a certain model set, one seeks in Optimal Recovery to recover this function in a way that minimizes the worst-case error…