Convex Relaxation Methods for Community Detection

نویسندگان

چکیده

This paper surveys recent theoretical advances in convex optimization approaches for community detection. We introduce some important techniques and results establishing the consistency of detection under various statistical models. In particular, we discuss basic based on primal dual analysis. also present that demonstrate several distinctive advantages detection, including robustness against outlier nodes, weak assortativity, adaptivity to heterogeneous degrees. survey is not intended be a complete overview vast literature this fast-growing topic. Instead, aim provide big picture remarkable development area make accessible broad audience. hope expository article can serve as an introductory guide readers who are interested using, designing, analyzing relaxation methods network

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ژورنال

عنوان ژورنال: Statistical Science

سال: 2021

ISSN: ['2168-8745', '0883-4237']

DOI: https://doi.org/10.1214/19-sts715