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Model-Driven Subspaces for Large-Scale Optimization with Local Approximation Strategy
Yitong He, Pengcheng Xie
Solving large-scale optimization problems is a bottleneck and is very important for machine learning and multiple kinds of scientific problems. Subspace-based methods using the loc…
ReMU: Regional Minimal Updating for Model-Based Derivative-Free Optimization
Pengcheng Xie, Stefan M. Wild
Derivative-free optimization (DFO) problems are optimization problems where derivative information is unavailable or extremely difficult to obtain. Model-based DFO solvers have bee…
On the Relationship between -poisedness in Derivative-Free Optimization and Outliers in Local Outlier Factor
Qi Zhang, Pengcheng Xie
Derivative-free optimization (DFO) is a method that does not require the calculation of gradients or higher-order derivatives of the objective function, making it suitable for case…
Sufficient Conditions for Error Distance Reduction in the (\ell^2)-norm Trust Region between Minimizers of Local Nonconvex Multivariate Quadratic Approximates
Pengcheng Xie
This paper analyzes the sufficient conditions for distance reduction between minimizers of local nonconvex quadratic approximate functions with diagonal Hessian in the (\ell^2)-nor…