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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…
math.OC2025
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…