Bayesian parameter estimation via variational methods
Statistics and Computing
Variational mixture of Bayesian independent component analyzers
Neural Computation
Factorial hidden Markov models and the generalized backfitting algorithm
Neural Computation
Factorial Markov Random Fields
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Dynamic Trees: Learning to Model Outdoor Scenes
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Non-linear Bayesian Image Modelling
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
A Dynamic Bayesian Network Approach to Tracking Using Learned Switching Dynamic Models
HSCC '00 Proceedings of the Third International Workshop on Hybrid Systems: Computation and Control
A Probabilistic Approach to High-Resolution Sleep Analysis
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches
Neural Processing Letters
Understanding belief propagation and its generalizations
Exploring artificial intelligence in the new millennium
LOGOS: a modular Bayesian model for de novo motif detection
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Hierarchy, priors and wavelets: structure and signal modelling using ICA
Signal Processing - Special issue on independent components analysis and beyond
"Ideal Parent" structure learning for continuous variable networks
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Graph partition strategies for generalized mean field inference
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
Background Segmentation Using Spatial-Temporal Multi-Resolution MRF
WACV-MOTION '05 Proceedings of the IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 - Volume 02
Learning Hidden Variable Networks: The Information Bottleneck Approach
The Journal of Machine Learning Research
An EM Algorithm for the Block Mixture Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Software failure prediction based on a Markov Bayesian network model
Journal of Systems and Software
Bayesian network based software reliability prediction with an operational profile
Journal of Systems and Software
Blind Source Separation by Sparse Decomposition in a Signal Dictionary
Neural Computation
A study of statistical models for query translation: finding a good unit of translation
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Creating probabilistic databases from information extraction models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Convergence Theorems for Generalized Alternating Minimization Procedures
The Journal of Machine Learning Research
Variational learning for rectified factor analysis
Signal Processing
A Bayesian belief network for IT implementation decision support
Decision Support Systems
Incremental learning of cognitive concepts: a hidden variable networks approach
PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots
Statistical query translation models for cross-language information retrieval
ACM Transactions on Asian Language Information Processing (TALIP)
Multi-Task Learning for Classification with Dirichlet Process Priors
The Journal of Machine Learning Research
Building Blocks for Variational Bayesian Learning of Latent Variable Models
The Journal of Machine Learning Research
Incremental Bayesian networks for structure prediction
Proceedings of the 24th international conference on Machine learning
Dynamic hierarchical Markov random fields and their application to web data extraction
Proceedings of the 24th international conference on Machine learning
A probabilistic graphical model for joint answer ranking in question answering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Expectation-maximization method for EEG-based continuous cursor control
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Distributed probabilistic inferencing in sensor networks using variational approximation
Journal of Parallel and Distributed Computing
Block clustering with Bernoulli mixture models: Comparison of different approaches
Computational Statistics & Data Analysis
Dynamic motion models in Monte Carlo Localization
Integrated Computer-Aided Engineering
Accurate max-margin training for structured output spaces
Proceedings of the 25th international conference on Machine learning
Bayesian Inference and Optimal Design for the Sparse Linear Model
The Journal of Machine Learning Research
Unsupervised learning of multilingual short message service (SMS) dialect from noisy examples
Proceedings of the second workshop on Analytics for noisy unstructured text data
Probabilistically Estimating Backbones and Variable Bias: Experimental Overview
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
The Journal of Machine Learning Research
Complex adaptive filtering user profile using graphical models
Information Processing and Management: an International Journal
A Bayesian Approach to Attention Control and Concept Abstraction
Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint
User grouping behavior in online forums
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
VARSAT: Integrating Novel Probabilistic Inference Techniques with DPLL Search
SAT '09 Proceedings of the 12th International Conference on Theory and Applications of Satisfiability Testing
A latent variable model for generative dependency parsing
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
Convexity arguments for efficient minimization of the Bethe and Kikuchi free energies
Journal of Artificial Intelligence Research
Graphical model inference in optimal control of stochastic multi-agent systems
Journal of Artificial Intelligence Research
On similarities between inference in game theory and machine learning
Journal of Artificial Intelligence Research
A unified approach to building hybrid recommender systems
Proceedings of the third ACM conference on Recommender systems
What kind of a graphical model is the brain?
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Variational Bayesian inference for a nonlinear forward model
IEEE Transactions on Signal Processing
Variational Bayesian blind deconvolution using a total variation prior
IEEE Transactions on Image Processing
Variational Bayesian sparse kernel-based blind image deconvolution with student's-t priors
IEEE Transactions on Image Processing
Variational decoding for statistical machine translation
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Statistical Methods and Models for Video-Based Tracking, Modeling, and Recognition
Foundations and Trends in Signal Processing
Robust Bayesian mixture modelling
Neurocomputing
Variational upper bounds for probabilistic phylogenetic models
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Smoothing LDA model for text categorization
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Message quantization in belief propagation: structural results in the low-rate regime
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Mean field variational approximation for continuous-time Bayesian networks
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Convexifying the Bethe free energy
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
The infinite hidden Markov random field model
IEEE Transactions on Neural Networks
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
FastInf: An Efficient Approximate Inference Library
The Journal of Machine Learning Research
Variational segmentation algorithms with label frequency constraints
Pattern Recognition and Image Analysis
Optimal control in large stochastic multi-agent systems
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Variational inference with graph regularization for image annotation
ACM Transactions on Intelligent Systems and Technology (TIST)
Conjugate mixture models for clustering multimodal data
Neural Computation
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
The Journal of Machine Learning Research
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
The Journal of Machine Learning Research
Incremental Sigmoid Belief Networks for Grammar Learning
The Journal of Machine Learning Research
Nonlinear relational markov networks with an application to the game of go
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Probabilistic index histogram for robust object tracking
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
A variational approximation for Bayesian networks with discrete and continuous latent variables
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Learning Bayesian networks with restricted causal interactions
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Variational learning in mixed-state dynamic graphical models
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Variational relevance vector machines
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Monte Carlo inference via greedy importance sampling
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
UAI'01 Proceedings of the Seventeenth 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
Mixture representations for inference and learning in Boltzmann machines
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Variational approximation for heteroscedastic linear models and matching pursuit algorithms
Statistics and Computing
Transductive gaussian process regression with automatic model selection
ECML'06 Proceedings of the 17th European conference on Machine Learning
Bayesian hierarchical mixtures of experts
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
The Information bottleneck EM algorithm
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
A generalized mean field algorithm for variational inference in exponential families
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
A possibilistic clustering approach toward generative mixture models
Pattern Recognition
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
Dynamic maps in monte carlo localization
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
Characterizing propagation methods for boolean satisfiability
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
A variational statistical framework for object detection
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Detecting MicroRNA targets by linking sequence, MicroRNA and gene expression data
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
Some aspects of latent structure analysis
SLSFS'05 Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection
A nonparametric Bayesian approach toward robot learning by demonstration
Robotics and Autonomous Systems
Variational conditional random fields for online speaker detection and tracking
Speech Communication
Eye movements as time-series random variables: A stochastic model of eye movement control in reading
Cognitive Systems Research
An efficient learning procedure for deep boltzmann machines
Neural Computation
A spatially-constrained normalized Gamma process prior
Expert Systems with Applications: An International Journal
Unsupervised learning on an approximate corpus
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Latent identity variables: biometric matching without explicit identity estimation
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
MedLDA: maximum margin supervised topic models
The Journal of Machine Learning Research
Nonparametric bayesian multitask collaborative filtering
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Probabilistic inference with noisy-threshold models based on a CP tensor decomposition
International Journal of Approximate Reasoning
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