Residual Expansion Algorithm: Fast and Effective Optimization for Nonconvex Least Squares Problems

Abstract

We propose the residual expansion (RE) algorithm: a global (or near-global) optimization method for nonconvex least squares problems. Unlike most existing nonconvex optimization techniques, the RE algorithm is not based on either stochastic or multi-point searches, therefore, it can achieve fast global optimization. Moreover, the RE algorithm is easy to… (More)
DOI: 10.1109/CVPR.2017.762

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