Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
An introduction to variational methods for graphical models
Learning in graphical models
Bayesian parameter estimation via variational methods
Statistics and Computing
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Expectation Propagation for approximate Bayesian inference
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
A Tighter Bound for Graphical Models
Neural Computation
LOGOS: a modular Bayesian model for de novo motif detection
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Graph partition strategies for generalized mean field inference
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Proceedings of the 25th international conference on Machine learning
A Joint Topic and Perspective Model for Ideological Discourse
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
Cluster Selection Based on Coupling for Gaussian Mean Fields
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Mixed Membership Stochastic Blockmodels
The Journal of Machine Learning Research
Dynamic mixed membership blockmodel for evolving networks
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
User grouping behavior in online forums
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A new dual wing harmonium model for document retrieval
Pattern Recognition
Artificial General Intelligence through Large-Scale, Multimodal Bayesian Learning
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Journal of Artificial Intelligence Research
Identifying news videos' ideological perspectives using emphatic patterns of visual concepts
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Message family propagation for ising mean field based on iteration tree
Proceedings of the 18th ACM conference on Information and knowledge management
A novel dual wing harmonium model aided by 2-D wavelet transform subbands for document data mining
Expert Systems with Applications: An International Journal
Combining stochastic block models and mixed membership for statistical network analysis
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
A combined expression-interaction model for inferring the temporal activity of transcription factors
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
Variational inference with graph regularization for image annotation
ACM Transactions on Intelligent Systems and Technology (TIST)
Stochastic Composite Likelihood
The Journal of Machine Learning Research
Learning to infer social ties in large networks
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Who will follow you back?: reciprocal relationship prediction
Proceedings of the 20th ACM international conference on Information and knowledge management
A patient-gene model for temporal expression profiles in clinical studies
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Structured Learning and Prediction in Computer Vision
Foundations and Trends® in Computer Graphics and Vision
Training factored PCFGs with expectation propagation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Employing hierarchical Bayesian networks in simple and complex emotion topic analysis
Computer Speech and Language
Learning to predict reciprocity and triadic closure in social networks
ACM Transactions on Knowledge Discovery from Data (TKDD)
Variational inference in nonconjugate models
The Journal of Machine Learning Research
Stochastic variational inference
The Journal of Machine Learning Research
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We present a ciass of generalized mean field (GMF) algorithms for approximate inference in exponential family graphical models which is analogous to the generalized belief propagation (GBP) or cluster variational methods. While those methods are based on overlapping clusters, our approach is based on nonoverlapping clusters. Unlike the cluster variational methods, the approach is proved to converge to a globally consistent set of marginals and a lower bound on the likelihood, while providing much of the flexibility associated with cluster variational methods. We present experiments that analyze the effect of different choices of clustering on inference quality, and compare GMF with belief propagation on several canonical models.