Recurrent sampling models for the Helmholtz machine
Neural Computation
An Introduction to Variational Methods for Graphical Models
Machine Learning
Reinforcement Learning with Factored States and Actions
The Journal of Machine Learning Research
An EM Algorithm for the Block Mixture Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchic Bayesian models for kernel learning
ICML '05 Proceedings of the 22nd international conference on Machine learning
A Variational Method for Learning Sparse and Overcomplete Representations
Neural Computation
A statistical framework for query translation disambiguation
ACM Transactions on Asian Language Information Processing (TALIP)
A parametric density model for blind source separation
Neural Processing Letters
Bayesian Inference and Optimal Design for the Sparse Linear Model
The Journal of Machine Learning Research
Joint Ranking for Multilingual Web Search
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Topic-link LDA: joint models of topic and author community
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Convex variational Bayesian inference for large scale generalized linear models
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Independent factor topic models
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Latent classification models for binary data
Pattern Recognition
Variational probabilistic inference and the QMR-DT network
Journal of Artificial Intelligence Research
Variational cumulant expansions for intractable distributions
Journal of Artificial Intelligence Research
Scalable diagnosis in IP networks using path-based measurement and inference: A learning framework
Journal of Visual Communication and Image Representation
Bayesian methods for fMRI time-series analysis using a nonstationary model for the noise
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
Super-Linear Convergence of Dual Augmented Lagrangian Algorithm for Sparsity Regularized Estimation
The Journal of Machine Learning Research
Learning to rank audience for behavioral targeting in display ads
Proceedings of the 20th ACM international conference on Information and knowledge management
A variational approximation for Bayesian networks with discrete and continuous latent variables
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Variational approximations between mean field theory and the junction tree algorithm
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Large deviation methods for approximate probabilistic inference
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
SIAM Journal on Imaging Sciences
Super-Gaussian mixture source model for ICA
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Stochastic variational inference
The Journal of Machine Learning Research
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