Classifying Big Data over Networks Via the Logistic Network Lasso

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openAccess

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Volume Title

A4 Artikkeli konferenssijulkaisussa

Date

2019-02-19

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Mcode

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Language

en

Pages

4
855-858

Series

2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, Volume 2018-October

Abstract

We apply network Lasso to solve binary classification and clustering problems on network structured data. In particular we generalize ordinary logistic regression to non-Euclidean data defined over a complex network structure. The resulting logistic network Lasso classifier amounts to solving a convex optimization problem. A scalable classification algorithm is obtained by applying the alternating direction methods of multipliers.

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Keywords

big data over networks, classification, clustering, complex networks, compressed sensing, convex optimization, semi-supervised learning

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Citation

Ambos, H, Tran, N & Jung, A 2019, Classifying Big Data over Networks Via the Logistic Network Lasso . in M B Matthews (ed.), 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS . vol. 2018-October, 8645260, IEEE, pp. 855-858, Asilomar Conference on Signals, Systems & Computers, Pacific Grove, United States, 28/10/2018 . https://doi.org/10.1109/ACSSC.2018.8645260