7 papers
Extrapolation-based Direct Search for Nonsmooth Stochastic Zeroth-Order Optimization
Anthony Palmieri, Francesco Rinaldi, Sara Shashaani
We propose and analyze a stochastic direct-search method for unconstrained zeroth-order minimization of locally Lipschitz, possibly nonsmooth, objectives. The method combines rando…
Adaptive Regularization within Trust Region Methods for Stochastic Nonconvex Optimization
Yunsoo Ha, Sara Shashaani, Quoc Tran-dinh
We propose a stochastic nonconvex optimization algorithm that achieves almost sure iteration complexity for problems with smooth objective function…
Stratified adaptive sampling for derivative-free stochastic trust-region optimization
Giovanni Amici, Sara Shashaani, Pranav Jain
There is emerging evidence that trust-region (TR) algorithms are very effective at solving derivative-free nonconvex stochastic optimization problems in which the objective functio…
Root Finding and Metamodeling for Rapid and Robust Computer Model Calibration
Yongseok Jeon, Sara Shashaani
We concern computer model calibration problem where the goal is to find the parameters that minimize the discrepancy between the multivariate real-world and computer model outputs.…
Complexity of Zeroth- and First-order Stochastic Trust-Region Algorithms
Yunsoo Ha, Sara Shashaani, Raghu Pasupathy
Model update (MU) and candidate evaluation (CE) are classical steps incorporated inside many stochastic trust-region (TR) algorithms. The sampling effort exerted within these steps…
Uncertainty Quantification using Simulation Output: Batching as an Inferential Device
Yongseok Jeon, Yi Chu, Raghu Pasupathy +1
We present batching as an omnibus device for uncertainty quantification using simulation output. We consider the classical context of a simulationist performing uncertainty quantif…