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Useful Compact Representations for Data-Fitting
March 20, 2024, 4:42 a.m. | Johannes J. Brust
cs.LG updates on arXiv.org arxiv.org
Abstract: For minimization problems without 2nd derivative information, methods that estimate Hessian matrices can be very effective. However, conventional techniques generate dense matrices that are prohibitive for large problems. Limited-memory compact representations express the dense arrays in terms of a low rank representation and have become the state-of-the-art for software implementations on large deterministic problems. We develop new compact representations that are parameterized by a choice of vectors and that reduce to existing well known formulas …
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