University of Science and Technology of China Reports Findings in Machine Learni ng (Machine Learning K-Means Clustering in Interpolative Separable Density Fitti ng Algorithm: Advancing Accurate and Efficient Cubic-Scaling Density Functional ...)

Robotics & Machine Learning Daily News2024，Issue(Mar.19) ：28-29.

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University of Science and Technology of China Reports Findings in Machine Learni ng (Machine Learning K-Means Clustering in Interpolative Separable Density Fitti ng Algorithm: Advancing Accurate and Efficient Cubic-Scaling Density Functional ...)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting out of Anhui, People’s Republic of China , by NewsRx editors, research stated, “Density functional perturbation theory (D FPT) is a crucial tool for accurately describing lattice dynamics. The adaptivel y compressed polarizability (ACP) method reduces the computational complexity of DFPT calculations from O() to O() by combining the interpolative separable dens ity fitting (ISDF) algorithm.”

Key words

Anhui/People’s Republic of China/Asia/Algorithms/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024

Robotics & Machine Learning Daily News

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