activity
20142026
most citedMost Convex Functions Have Unique Minimizers

6 citations · 14 across the 18 of their papers we have counts for

collaborators

19 papers

math.OC2026

The cosine measure of a function at a point

Warren Hare, Gabriel Jarry-Bolduc, Chayne Planiden

The cosine measure of a set of vectors in measures how well the set covers all directions in . It identifies the direction furthest, in angle, from the…

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.OC2021

Nicely structured positive bases with maximal cosine measure

Warren Hare, Gabriel Jarry-Bolduc, Chayne Planiden

The properties of positive bases make them a useful tool in derivative-free optimization (DFO) and an interesting concept in mathematics. The notion of the \emph{cosine measure} he…

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.OC2020

Hessian approximations

Warren Hare, Gabriel Jarry-Bolduc, Chayne Planiden

This work introduces the nested-set Hessian approximation, a second-order approximation method that can be used in any derivative-free optimization routine that requires such infor…

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…