383 citations · 432 across the 16 of their papers we have counts for
5 papers · 1 filter
A Feasible Direction Method with Active-Set Identification for Derivative-Free Optimization
Jeffrey Larson, Matt Menickelly, Lara Zebiane
We propose a model-based trust region method for derivative-free optimization with simulation-based inequality constraints. We are motivated by settings of simulation optimization…
Edge-Aligned Beam Placement in Scanning Probe Tomography via Reconstruction-Free Sequential Design of Experiments
San Dinh, Zichao Wendy Di, Matt Menickelly
In X-ray scanning probe tomography, reconstruction quality generally improves with larger numbers of projections. However, additional projections increase experiment costs, acquisi…
Discrepancy Modeling with Intermediate Variables: A New Framework for Robust Gaussian Process Calibration
Henry Shaowu Yuchi, Michael Grosskopf, Aman Sharma +4
Gaussian processes are widely used for surrogate modeling in computer experiments, which often produce numerous intermediate variables that are not explicitly used in standard cali…
Birkhoff interpolation models for optimization with some available derivatives
Jeffrey Larson, Matt Menickelly, Evan Toler
We consider interpolation-based derivative-free optimization in settings where only some derivatives are available. Such situations arise in scientific computing applications invol…
Importance Sampling in Expensive Finite-Sum Optimization via Contextual Bandit Methods
Matt Menickelly
In computational science workflows, it is often the case that 1) objective functions for optimization involve multiple simulation outputs, and 2) those simulations can be performed…