Distributed user profiling via spectral methods

DOI10.1214/11-SSY036zbMath1315.68024arXiv1109.3318OpenAlexW2087974773MaRDI QIDQ2921183

Dan-Cristian Tomozei, Laurent Massoulié

Publication date: 7 October 2014

Full work available at URL: https://arxiv.org/abs/1109.3318

zbMATH Keywords

spectral decompositionrandom matrixmessage passingdistributed recommendation systemdistributed spectral embedding

Mathematics Subject Classification ID

Computing methodologies for information systems (hypertext navigation, interfaces, decision support, etc.) (68U35) Random matrices (algebraic aspects) (15B52) Distributed systems (68M14) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)

Related Items (3)

On semidefinite relaxations for the block model ⋮ Collaborative filtering with information-rich and~information-sparse entities ⋮ A spectral method for community detection in moderately sparse degree-corrected stochastic block models

Cites Work

• Oja's algorithm for graph clustering, Markov spectral decomposition, and risk sensitive control
• On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix
• On the Early History of the Singular Value Decomposition
• Spectral techniques applied to sparse random graphs
• Spectral Clustering by Recursive Partitioning
• A decentralized algorithm for spectral analysis
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