Del i serien Lecture Notes in Computer Science

Statistical Network Analysis: Models, Issues, and New Directions

ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers

Häftad, Engelska, 2007

AvEdoardo M. Airoldi,David M. Blei,Stephen E. Fienberg,Anna Goldenberg,Eric P. Xing,Alice X. Zheng

719 kr

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This volume was prepared to share with a larger audience the exciting ideas and work presented at an ICML 2006 workshop of the same title. Our goal in organ- ing the workshop was to encourage a dialog among people coming from di?erent disciplinary perspectives and with di?erent methods, models, and tools.

Produktinformation

Utgivningsdatum2007-07-20
Mått155 x 235 x 17 mm
Vikt328 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor200
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783540731320

Tillhör följande kategorier

Nätverk och kommunikation inom Data och IT

Invited Presentations.- Structural Inference of Hierarchies in Networks.- Heider vs Simmel: Emergent Features in Dynamic Structures.- Joint Group and Topic Discovery from Relations and Text.- Statistical Models for Networks: A Brief Review of Some Recent Research.- Other Presentations.- Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis.- Exploratory Study of a New Model for Evolving Networks.- A Latent Space Model for Rank Data.- A Simple Model for Complex Networks with Arbitrary Degree Distribution and Clustering.- Discrete Temporal Models of Social Networks.- Approximate Kalman Filters for Embedding Author-Word Co-occurrence Data over Time.- Discovering Functional Communities in Dynamical Networks.- Empirical Analysis of a Dynamic Social Network Built from PGP Keyrings.- Extended Abstracts.- A Brief Survey of Machine Learning Methods for Classification in Networked Data and an Application to Suspicion Scoring.- Age and Geographic Inferences of the LiveJournal Social Network.- Inferring Organizational Titles in Online Communication.- Learning Approximate MRFs from Large Transactional Data.- Panel Discussion.- Panel Discussion.

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