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Adaptive Sampling Trust Region Optimization for Derivative-free Stochastic Functions and Deterministic Equality Constraints
Nicole Felice, Sara Shashaani, Lindon Roberts
We study optimization problems with noisy zeroth-order objective observations and deterministic nonlinear equality constraints with available derivatives. We propose a constrained…
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 functions…
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…
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…
Two-Stage Estimation and Variance Modeling for Latency-Constrained Variational Quantum Algorithms
Yunsoo Ha, Sara Shashaani, Matt Menickelly
The Quantum Approximate Optimization Algorithm (QAOA) has enjoyed increasing attention in noisy intermediate-scale quantum computing due to its application to combinatorial optimiz…