most citedA Stochastic Quasi-Newton Method in the Absence of Common Random Numbers

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

math.OC2023

Avoiding Geometry Improvement in Derivative-Free Model-Based Methods via Randomization

Matt Menickelly

We present a technique for model-based derivative-free optimization called \emph{basis sketching}. Basis sketching consists of taking random sketches of the Vandermonde matrix empl…

math.OC2023★ 2 cited

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers

Matt Menickelly, Stefan M. Wild, Miaolan Xie

We present a quasi-Newton method for unconstrained stochastic optimization. Most existing literature on this topic assumes a setting of stochastic optimization in which a finite su…