Adaptive Step Size Strategy for Orthogonality Constrained Line Search Methods Article Swipe

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Xiaoying Dai , Liwei Zhang , Aihui Zhou ·

YOU? · · 2019 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1906.02883

In this paper, we propose an adaptive step size strategy for a class of line search methods for orthogonality constrained minimization problems, which avoids the classic backtracking procedure. We prove the convergence of the line search methods equipped with our adaptive step size strategy under some mild assumptions.We then apply the adaptive algorithm to electronic structure calculations, which show that our strategy is efficient and recommended.

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Artificial Intelligence

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Orthogonality Backtracking Line search Computer science Convergence (economics) Mathematical optimization Line (geometry) Class (philosophy) Adaptive strategies Minification Algorithm Mathematics Artificial intelligence Path (computing) Geometry Programming language Archaeology History Economics Economic growth

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/1906.02883
PDF: https://arxiv.org/pdf/1906.02883
OA Status: green
Cited By: 4
References: 32
Related Works: 10
OpenAlex ID: https://openalex.org/W2948518813

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DOI: https://doi.org/10.48550/arxiv.1906.02883

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Title: Adaptive Step Size Strategy for Orthogonality Constrained Line Search Methods

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Type: preprint

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Language: en

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Publication year: 2019

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Publication date: 2019-06-07

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Authors: Xiaoying Dai, Liwei Zhang, Aihui Zhou

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Landing page: https://arxiv.org/abs/1906.02883

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PDF URL: https://arxiv.org/pdf/1906.02883

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Concepts: Orthogonality, Backtracking, Line search, Computer science, Convergence (economics), Mathematical optimization, Line (geometry), Class (philosophy), Adaptive strategies, Minification, Algorithm, Mathematics, Artificial intelligence, Path (computing), Geometry, Programming language, Archaeology, History, Economics, Economic growth

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Cited by: 4

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Citations by year (recent): 2024: 1, 2023: 1, 2020: 2

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References (count): 32

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Related works (count): 10

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