Estimating Higher-Order Mixed Memberships via the ℓ2,∞ Tensor Perturbation Bound

IF 3 1区数学 Q1 STATISTICS & PROBABILITY Journal of the American Statistical Association Pub Date : 2024-09-23 DOI:10.1080/01621459.2024.2404265

Joshua Agterberg, Anru R. Zhang

引用次数: 0

Abstract

Higher-order multiway data is ubiquitous in machine learning and statistics and often exhibits community-like structures, where each component (node) along each different mode has a community membe...

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通过 ℓ2,∞ 张量扰动约束估算高阶混合成员资格

高阶多路数据在机器学习和统计中无处不在，并且经常表现出类似于社区的结构，其中每个不同模式的每个组件（节点）都有一个社区成员。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of the American Statistical Association 数学-统计学与概率论

CiteScore

7.50

自引率

8.10%

发文量

168

审稿时长

12 months

期刊介绍： Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods in economic, social, physical, engineering, and health sciences. Important books contributing to statistical advancement are reviewed in JASA . JASA is indexed in Current Index to Statistics and MathSci Online and reviewed in Mathematical Reviews. JASA is abstracted by Access Company and is indexed and abstracted in the SRM Database of Social Research Methodology.

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