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Spectral Counting of Triangles in Power-Law Networks via Element-Wise Sparsification Charalampos E. Tsourakakis School of Computer Science Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA
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Document Date: 2011-03-02 23:55:07

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Cambridge University Press / Las Vegas NV / Intel / Reuters / Power-Law Networks / /

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Mellon University / Computer Science Carnegie Mellon University / Eirinaios Michelakis EECS University of California / Computer Science Rensselaer Polytechnic Institute / Soda Hall / /

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graph mining / orward algorithm / graph mining applications / database systems / real-world networks / large networks / large real networks / approximation algorithms / semicircle law / semi-streaming algorithms / eigenvalue power law / rank approximation algorithm / internet topology / random power law graphs / streaming algorithms / large powerlaw network / power law / computing / real world networks / parallelizable algorithm / approximate solutions / montecarlo algorithms / /

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Cambridge University / Christos Faloutsos School / Element-Wise Sparsification Charalampos E. Tsourakakis School / Ioannis Koutis School of Computer Science Carnegie / Mellon University / University of California / Berkeley / Society for Industrial and Applied Mathematics / American Society for Information Science / Petros Drineas School / Rensselaer Polytechnic Institute / Carnegie Mellon University / /

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Maryland / New York / Pennsylvania / /

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Journal of Cognitive Neuroscience / /

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Achlioptas-McSherry algorithms / Neuroscience / Streaming Algorithms / orward algorithm / semi-streaming algorithms / two approximation algorithms / proposed algorithm / TERATOR algorithm / RIANGLE algorithm / low rank approximation algorithm / /

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