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Spectral Conjugate Gradient Variant Built via Least-Squares Quasi-Newton Update
A new arXiv paper introduces a three-term spectral modification of the Hestenes-Stiefel conjugate gradient method, derived using least-squares approximations of a modified quasi-Newton update. The approach aims to retain the algorithm's resistance to jamming while guaranteeing sufficient descent. The authors apply it to a revised robust binary classification model.