102 citations · 164 across the 17 of their papers we have counts for
6 papers · 1 filter
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…
Optimal Recovery from Inaccurate Data in Hilbert Spaces: Regularize, but what of the Parameter?
Simon Foucart, Chunyang Liao
In Optimal Recovery, the task of learning a function from observational data is tackled deterministically by adopting a worst-case perspective tied to an explicit model assumption…
Instances of Computational Optimal Recovery: Refined Approximability Models
Simon Foucart
Models based on approximation capabilities have recently been studied in the context of Optimal Recovery. These models, however, are not compatible with overparametrization, since…
Instances of Computational Optimal Recovery: Dealing with Observation Errors
Mahmood Ettehad, Simon Foucart
When attempting to recover functions from observational data, one naturally seeks to do so in an optimal manner with respect to some modeling assumption. With a focus put on the wo…
Computation of Chebyshev Polynomials for Union of Intervals
Simon Foucart, Jean-Bernard Lasserre
Chebyshev polynomials of the first and second kind for a set K are monic polynomials with minimal L -and L 1-norm on K, respectively. This articles presents numerical proce…
Approximability Models and Optimal System Identification
Mahmood Ettehad, Simon Foucart
This article considers the problem of optimally recovering stable linear time-invariant systems observed via linear measurements made on their transfer functions. A common modeling…