research-article

Dynamic mixed membership blockmodel for evolving networks

Authors:

Wenjie Fu,

Le Song,

Eric P. XingAuthors Info & Claims

ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning

Pages 329 - 336

https://doi.org/10.1145/1553374.1553416

Published: 14 June 2009 Publication History

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Abstract

In a dynamic social or biological environment, interactions between the underlying actors can undergo large and systematic changes. Each actor can assume multiple roles and their degrees of affiliation to these roles can also exhibit rich temporal phenomena. We propose a state space mixed membership stochastic blockmodel which can track across time the evolving roles of the actors. We also derive an efficient variational inference procedure for our model, and apply it to the Enron email networks, and rewiring gene regulatory networks of yeast. In both cases, our model reveals interesting dynamical roles of the actors.

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Cited By

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Liu XSong WMusial KLi YZhao XYang B(2025)Stochastic Block Models for Complex Network Analysis: A SurveyACM Transactions on Knowledge Discovery from Data10.1145/371307619:3(1-35)Online publication date: 22-Jan-2025
https://dl.acm.org/doi/10.1145/3713076
Kumar MSingh NBiswas B(2025)PQKELPExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.125944265:COnline publication date: 15-Mar-2025
https://dl.acm.org/doi/10.1016/j.eswa.2024.125944
Kumar MMishra SSingh SBiswas B(2024)Community-enhanced Link Prediction in Dynamic NetworksACM Transactions on the Web10.1145/358051318:2(1-32)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3580513
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Index Terms

Dynamic mixed membership blockmodel for evolving networks
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Model verification and validation
      2. Modeling methodologies
2. Mathematics of computing
  1. Probability and statistics
    1. Stochastic processes

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Published In

ICML '09: Proceedings of the 26th Annual International Conference on Machine Learning

June 2009

1331 pages

ISBN:9781605585161

DOI:10.1145/1553374

General Chair:
Andrea Danyluk
Williams College
,
Program Chairs:
Léon Bottou
NEC Laboratories America
,
Michael Littman
Rutgers University

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 June 2009

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ICML '09

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Microsoft Research

ICML '09: The 26th Annual International Conference on Machine Learning held in conjunction with the 2007 International Conference on Inductive Logic Programming

June 14 - 18, 2009

Quebec, Montreal, Canada

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Overall Acceptance Rate 140 of 548 submissions, 26%

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Liu XSong WMusial KLi YZhao XYang B(2025)Stochastic Block Models for Complex Network Analysis: A SurveyACM Transactions on Knowledge Discovery from Data10.1145/371307619:3(1-35)Online publication date: 22-Jan-2025
https://dl.acm.org/doi/10.1145/3713076
Kumar MSingh NBiswas B(2025)PQKELPExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.125944265:COnline publication date: 15-Mar-2025
https://dl.acm.org/doi/10.1016/j.eswa.2024.125944
Kumar MMishra SSingh SBiswas B(2024)Community-enhanced Link Prediction in Dynamic NetworksACM Transactions on the Web10.1145/358051318:2(1-32)Online publication date: 8-Jan-2024
https://dl.acm.org/doi/10.1145/3580513
Ke ZWang J(2024)Optimal Network Membership Estimation under Severe Degree HeterogeneityJournal of the American Statistical Association10.1080/01621459.2024.2388903(1-28)Online publication date: 13-Aug-2024
https://doi.org/10.1080/01621459.2024.2388903
Modell AGallagher ICeccherini EWhiteley NRubin-Delanchy POh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Intensity profile projectionProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3667131(23259-23296)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3666122.3667131
Daniel Loyal JChen Y(2023)A Bayesian Nonparametric Latent Space Approach to Modeling Evolving Communities in Dynamic NetworksBayesian Analysis10.1214/21-BA130018:1Online publication date: 1-Mar-2023
https://doi.org/10.1214/21-BA1300
Naik CCaron FRousseau JTeh YPalla K(2023)Bayesian Nonparametrics for Sparse Dynamic NetworksMachine Learning and Knowledge Discovery in Databases10.1007/978-3-031-26419-1_12(191-206)Online publication date: 17-Mar-2023
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Shin HPark JKang D(2022)A Graph-Cut-Based Approach to Community Detection in NetworksApplied Sciences10.3390/app1212621812:12(6218)Online publication date: 18-Jun-2022
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Durbeck LAthanas P(2022)Kalman Filter Driven Estimation of Community Structure in Time Varying Graphs2022 IEEE High Performance Extreme Computing Conference (HPEC)10.1109/HPEC55821.2022.9926358(1-7)Online publication date: 19-Sep-2022
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Riverain PFossier SNadif M(2022)Poisson degree corrected dynamic stochastic block modelAdvances in Data Analysis and Classification10.1007/s11634-022-00492-917:1(135-162)Online publication date: 27-Feb-2022
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Mixed-membership naive Bayes models

Discriminative Mixed-Membership Models

Evolving gene regulatory networks: a sensitivity-based approach

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