Matt Menickelly

According to our database, Matt Menickelly authored at least 24 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

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

Matt Menickelly, Stefan M. Wild, Miaolan Xie

J. Optim. Theory Appl., February, 2026

HFBTHO-AD: Differentiation of a nuclear energy density functional code.

Laurent Hascoët, Matt Menickelly, Sri Hari Krishna Narayanan, Jared O'Neal, Nicolas Schunck, Stefan M. Wild

Comput. Phys. Commun., 2026

2025

A Novel Noise-Aware Classical Optimizer for Variational Quantum Algorithms.

Jeffrey Larson, Matt Menickelly, Jiahao Shi

INFORMS J. Comput., 2025

Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms.

Yunsoo Ha, Sara Shashaani, Matt Menickelly

INFORMS J. Comput., 2025

Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization.

Dzung T. Phan, Matt Menickelly, Tsuyoshi Idé, Jayant Kalagnanam

Proceedings of the 2025 SIAM International Conference on Data Mining, 2025

A Noise-Aware Scalable Subspace Classical Optimizer for the Quantum Approximate Optimization Algorithm.

Kwassi Joseph Dzahini, Jeffrey M. Larson, Matt Menickelly, Stefan M. Wild

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2025

2024

Stochastic average model methods.

Matt Menickelly, Stefan M. Wild

Comput. Optim. Appl., June, 2024

Structure-aware methods for expensive derivative-free nonsmooth composite optimization.

Jeffrey Larson, Matt Menickelly

Math. Program. Comput., 2024

2023

Latency considerations for stochastic optimizers in variational quantum algorithms.

Matt Menickelly, Yunsoo Ha, Matthew Otten

Quantum, March, 2023

2022

Improving PyDDA's atmospheric wind retrievals using automatic differentiation and Augmented Lagrangian methods.

Robert Jackson, Rebecca Gjini, Sri Hari Krishna Narayanan, Matt Menickelly, Paul D. Hovland, Jan Hückelheim, Scott M. Collis

Proceedings of the 21st Python in Science Conference, 2022

TROPHY: Trust Region Optimization Using a Precision Hierarchy.

Richard J. Clancy, Matt Menickelly, Jan Hückelheim, Paul D. Hovland, Prani Nalluri, Rebecca Gjini

Proceedings of the Computational Science - ICCS 2022, 2022

2021

Tuning Multigrid Methods with Robust Optimization and Local Fourier Analysis.

Jed Brown, Yunhui He, Scott P. MacLachlan, Matt Menickelly, Stefan M. Wild

SIAM J. Sci. Comput., 2021

Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions.

Jeffrey Larson, Matt Menickelly, Baoyu Zhou

SIAM J. Optim., 2021

Optimal decision trees for categorical data via integer programming.

Oktay Günlük, Jayant Kalagnanam, Minhan Li, Matt Menickelly, Katya Scheinberg

J. Glob. Optim., 2021

On the Solution of <i>ℓ</i>₀-Constrained Sparse Inverse Covariance Estimation Problems.

Dzung T. Phan, Matt Menickelly

INFORMS J. Comput., 2021

2020

Derivative-free robust optimization by outer approximations.

Matt Menickelly, Stefan M. Wild

Math. Program., 2020

A survey of nonlinear robust optimization.

Sven Leyffer, Matt Menickelly, Todd S. Munson, Charlie Vanaret, Stefan M. Wild

INFOR Inf. Syst. Oper. Res., 2020

Tuning Multigrid Methods with Robust Optimization.

Jed Brown, Yunhui He, Scott P. MacLachlan, Matt Menickelly, Stefan M. Wild

CoRR, 2020

2019

Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales.

Jose H. Blanchet, Coralia Cartis, Matt Menickelly, Katya Scheinberg

INFORMS J. Optim., April, 2019

Derivative-free optimization methods.

Jeffrey Larson, Matt Menickelly, Stefan M. Wild

Acta Numer., 2019

2018

Stochastic optimization using a trust-region method and random models.

Ruobing Chen, Matt Menickelly, Katya Scheinberg

Math. Program., 2018

2017

A Novel l0-Constrained Gaussian Graphical Model for Anomaly Localization.

Dzung T. Phan, Tsuyoshi Idé, Jayant Kalagnanam, Matt Menickelly, Katya Scheinberg

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

2016

Manifold Sampling for ℓ₁ Nonconvex Optimization.

Jeffrey Larson, Matt Menickelly, Stefan M. Wild

SIAM J. Optim., 2016

Optimal Generalized Decision Trees via Integer Programming.

Matt Menickelly, Oktay Günlük, Jayant Kalagnanam, Katya Scheinberg

CoRR, 2016