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Detecting Network Cliques with Radon Basis Pursuit

Author(s): Jiang, Xiaoye; Yao, Yuan; Liu, Han; Guibas, Leonidas

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Abstract: In this paper, we propose a novel formulation of the network clique detection problem by introducing a general network data representation framework. We show connections between our formulation with a new algebraic tool, namely Radon basis pursuit in homogeneous spaces. Such a connection allows us to identify rigorous recovery conditions for clique detection problems. Practical approximation algorithms are also developed for solving empirical problems and their usefulness is demonstrated on real-world datasets. Our work connects two seemingly different areas: network data analysis and compressed sensing, which helps to bridge the gap between the research of network data and the classical theory of statistical learning and signal processing.
Publication Date: 2012
Citation: Jiang, Xiaoye, Yuan Yao, Han Liu, and Leonidas Guibas. "Detecting network cliques with radon basis pursuit." Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, PMLR 22 (2012): 565-573.
ISSN: 2640-3498
Pages: 565 - 573
Type of Material: Conference Article
Series/Report no.: Proceedings of Machine Learning Research;
Journal/Proceeding Title: Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics
Version: Final published version. This is an open access article.

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