Detecting Network Cliques with Radon Basis Pursuit

11 years 6 months ago

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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.

Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guiba

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