5 papers
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…
Low-Order Explicit Hessian Imitation Method for Large-Scale Supervised Machine Learning
Yunlang Zhu, Lingjun Guo, Zahra Khatti +4
An algorithm is proposed for solving optimization problems arising in neural network training for supervised learning. The unique feature of the algorithm is the use of an auxiliar…
A Gradient Sampling Algorithm for Noisy Nonsmooth Nonconvex Optimization
Albert S. Berahas, Frank E. Curtis, Lara Zebiane
An algorithm is proposed, analyzed, and tested for minimizing locally Lipschitz objective functions that may be nonconvex and/or nonsmooth. The algorithm, which is built upon the g…
Active-Set Identification in Noisy and Stochastic Optimization
Frank E. Curtis, Daniel P. Robinson, Lara Zebiane
Identifying active constraints from a point near a local minimizer is important both theoretically and practically in constrained continuous optimization as it can help identify op…
NonOpt: Nonconvex, Nonsmooth Optimizer
Frank E. Curtis, Lara Zebiane
NonOpt, a C++ software package for minimizing locally Lipschitz objective functions, is presented. The software is intended primarily for minimizing objective functions that are no…