Neural Computation
A practical Bayesian framework for backpropagation networks
Neural Computation
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
Efficient Approximations for the MarginalLikelihood of Bayesian Networks with Hidden Variables
Machine Learning - Special issue on learning with probabilistic representations
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
A view of the EM algorithm that justifies incremental, sparse, and other variants
Proceedings of the NATO Advanced Study Institute on Learning in graphical models
Choice of Basis for Laplace Approximation
Machine Learning
Learning nonlinear overcomplete representations for efficient coding
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Neural Computation
Mean field theory for sigmoid belief networks
Journal of Artificial Intelligence Research
The Bayesian structural EM algorithm
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
An introduction to hidden Markov models and Bayesian networks
Hidden Markov models
Variational mixture of Bayesian independent component analyzers
Neural Computation
Non-linear Bayesian Image Modelling
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Incremental Sparse Kernel Machine
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
A Probabilistic Approach to High-Resolution Sleep Analysis
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Variational learning of clusters of undercomplete nonsymmetric independent components
The Journal of Machine Learning Research
The em algorithm for kernel matrix completion with auxiliary data
The Journal of Machine Learning Research
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Lack of Consistency of Mean Field and Variational break Bayes Approximations for State Space Models
Neural Processing Letters
One-Shot Learning of Object Categories
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Slow Convergence of EM and VBEM in Low-Noise Linear Models
Neural Computation
Online Model Selection Based on the Variational Bayes
Neural Computation
Computer Vision and Image Understanding
Variational approximations in Bayesian model selection for finite mixture distributions
Computational Statistics & Data Analysis
Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation
The Journal of Machine Learning Research
Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Stochastic complexity for mixture of exponential families in generalized variational Bayes
Theoretical Computer Science
Hierarchical Bayesian Inference of Brain Activity
Neural Information Processing
Upper bound for variational free energy of Bayesian networks
Machine Learning
Analysis of Variational Bayesian Matrix Factorization
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Variational Bayes for estimating the parameters of a hidden Potts model
Statistics and Computing
Letters: A novel view of the variational Bayesian clustering
Neurocomputing
Variational Bayes via propositionalized probability computation in PRISM
Annals of Mathematics and Artificial Intelligence
A note on variational Bayesian factor analysis
Neural Networks
Generalization error of linear neural networks in an empirical bayes approach
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IEEE Transactions on Evolutionary Computation
A variational multi-view learning framework and its application to image segmentation
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Variational Bayesian mixture model on a subspace of exponential family distributions
IEEE Transactions on Neural Networks
Robust Bayesian mixture modelling
Neurocomputing
Prior hyperparameters in Bayesian PCA
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Generalization error of automatic relevance determination
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Person name disambiguation in web pages using social network, compound words and latent topics
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Improving the robustness to outliers of mixtures of probabilistic PCAs
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Quantum annealing for variational Bayes inference
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Action oriented Bayesian learning of the operating space for a humanoid robot
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Track-based self-supervised classification of dynamic obstacles
Autonomous Robots
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing
The Journal of Machine Learning Research
Entropy-based variational scheme for fast bayes learning of Gaussian mixtures
SSPR&SPR'10 Proceedings of the 2010 joint IAPR international conference on Structural, syntactic, and statistical pattern recognition
Learning Non-linear Multivariate Dynamics of Motion in Robotic Manipulators
International Journal of Robotics Research
Semiparametric bivariate Archimedean copulas
Computational Statistics & Data Analysis
Variational bayes for modeling score distributions
Information Retrieval
Detection of hidden structures in nonstationary spike trains
Neural Computation
Likelihood-free Bayesian estimation of multivariate quantile distributions
Computational Statistics & Data Analysis
Active Machine Learning for Consideration Heuristics
Marketing Science
Blind source separation with time series variational Bayes expectation maximization algorithm
Digital Signal Processing
Theoretical Analysis of Bayesian Matrix Factorization
The Journal of Machine Learning Research
A new variational Bayesian algorithm with application to human mobility pattern modeling
Statistics and Computing
Analytic solution of hierarchical variational bayes in linear inverse problem
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Variational bayesian methods for audio indexing
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Stochastic complexity for mixture of exponential families in variational bayes
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Bayesian independent component analysis with prior constraints: an application in biosignal analysis
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Variational bayes estimation of mixing coefficients
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
Free energy of stochastic context free grammar on variational bayes
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Robots that learn language: developmental approach to human-machine conversations
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
Upper bounds for variational stochastic complexities of bayesian networks
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Variational conditional random fields for online speaker detection and tracking
Speech Communication
Global analytic solution of fully-observed variational Bayesian matrix factorization
The Journal of Machine Learning Research
Stochastic variational inference
The Journal of Machine Learning Research
QUAC: Quick unsupervised anisotropic clustering
Pattern Recognition
Learning finite Beta-Liouville mixture models via variational bayes for proportional data clustering
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A survey on latent tree models and applications
Journal of Artificial Intelligence Research
Fast topic discovery from web search streams
Proceedings of the 23rd international conference on World wide web
International Journal of Speech Technology
Structural Bayesian Linear Regression for Hidden Markov Models
Journal of Signal Processing Systems
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Current methods for learning graphical models with latent variables and a fixed structure estimate optimal values for the model parameters. Whereas this approach usually produces overfitting and suboptimal generalization performance, carrying out the Bayesian program of computing the full posterior distributions over the parameters remains a difficult problem. Moreover, learning the structure of models with latent variables, for which the Bayesian approach is crucial, is yet a harder problem. In this paper I present the Variational Bayes framework, which provides a solution to these problems. This approach approximates full posterior distributions over model parameters and structures, as well as latent variables, in an analytical manner without resorting to sampling methods. Unlike in the Laplace approximation, these posteriors are generally non-Gaussian and no Hessian needs to be computed. The resulting algorithm generalizes the standard Expectation Maximization algorithm, and its convergence is guaranteed. I demonstrate that this algorithm can be applied to a large class of models in several domains, including unsupervised clustering and blind source separation.