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20202026
most citedError Analysis of Surrogate Models Constructed through Operations on Sub-models

3 citations · 3 across the 13 of their papers we have counts for

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6 papers · 1 filter

math.NA2026

A -step generalization of the Q-order of convergence

Gabriel Jarry-Bolduc

The notion of Q-order convergence is arguably the most important tool for describing the asymptotic behavior of a convergent sequence. Loosely speaking, it captures the``speed''of…

math.NA2023

Using generalized simplex methods to approximate derivatives

Gabriel Jarry-Bolduc, Chayne Planiden

This paper presents two methods for approximating a proper subset of the entries of a Hessian using only function evaluations. These approximations are obtained using the technique…

math.NA2023

Using orthogonally structured positive bases for constructing positive -spanning sets with cosine measure guarantees

Warren Hare, Gabriel Jarry-Bolduc, Sébastien Kerleau +1

Positive spanning sets span a given vector space by nonnegative linear combinations of their elements. These have attracted significant attention in recent years, owing to their ex…

math.NA2021

Approximating the diagonal of a Hessian: which sample set of points should be used

Gabriel Jarry-Bolduc

An explicit formula to approximate the diagonal entries of the Hessian is introduced. When the derivative-free technique called \emph{generalized centered simplex gradient} is used…

math.NA2021

Limiting behaviour of the generalized simplex gradient as the number of points tends to infinity on a fixed shape in R^n

Warren Hare, Gabriel Jarry-Bolduc, Chayne Planiden

This work investigates the asymptotic behaviour of the gradient approximation method called the generalized simplex gradient (GSG). This method has an error bound that at first gla…

math.NA2020

Error bounds for overdetermined and underdetermined generalized centred simplex gradients

Warren Hare, Gabriel Jarry--Bolduc, Chayne Planiden

Using the Moore--Penrose pseudoinverse, this work generalizes the gradient approximation technique called centred simplex gradient to allow sample sets containing any number of poi…