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Probabilistic reasoning in intelligent systems: networks of plausible inference
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Introduction to algorithms
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Neural Computation
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Knowledge representation and inference in similarity networks and Bayesian multinets
Artificial Intelligence
Probabilistic independence networks for hidden Markov probability models
Neural Computation
Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
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Statistical methods for speech recognition
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A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
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Learning in graphical models
Stochastic Complexity in Statistical Inquiry Theory
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Probabilistic Networks and Expert Systems
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A Guide to the Literature on Learning Probabilistic Networks from Data
IEEE Transactions on Knowledge and Data Engineering
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Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Tractable Bayesian Learning of Tree Belief Networks
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
The FERET Evaluation Methodology for Face-Recognition Algorithms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Learning with mixtures of trees
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Competition and multiple cause models
Neural Computation
Cached sufficient statistics for efficient machine learning with large datasets
Journal of Artificial Intelligence Research
The Bayesian structural EM algorithm
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Probabilistic Methods for Finding People
International Journal of Computer Vision
A new Bayesian tree learning method with reduced time and space complexity
Fundamenta Informaticae
A Probabilistic Framework for the Hierarchic Organisation and Classification of Document Collections
Journal of Intelligent Information Systems
Latent class models for classification
Computational Statistics & Data Analysis
Mining Bayesian Network Structure for Large Sets of Variables
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Unsupervised Learning of Human Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning multiple evolutionary pathways from cross-sectional data
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Conditional Chow-Liu tree structures for modeling discrete-valued vector time series
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Very large Bayesian multinets for text classification
Future Generation Computer Systems
Naive Bayes models for probability estimation
ICML '05 Proceedings of the 22nd international conference on Machine learning
Dependency trees in sub-linear time and bounded memory
The VLDB Journal — The International Journal on Very Large Data Bases
Learning Image Components for Object Recognition
The Journal of Machine Learning Research
Proceedings of the 24th international conference on Machine learning
Finding low-entropy sets and trees from binary data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Image and Vision Computing
Labeling of Human Motion by Constraint-Based Genetic Algorithm
Computational Intelligence and Security
Taking the bite out of automated naming of characters in TV video
Image and Vision Computing
Speaker recognition with mixtures of Gaussians with sparse regression matrices
HLT-SRWS '04 Proceedings of the Student Research Workshop at HLT-NAACL 2004
Integrative construction and analysis of condition-specific biological networks
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Very large Bayesian multinets for text classification
Future Generation Computer Systems
Finite mixture model of bounded semi-naive Bayesian networks classifier
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Boosted multiple deformable trees for parsing human poses
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
A new approach to construct optimal bow tie diagrams for risk analysis
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
International Journal of Computer Vision
A game theoretic approach for feature clustering and its application to feature selection
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates
The Journal of Machine Learning Research
Efficiently approximating Markov tree bagging for high-dimensional density estimation
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Staged mixture modelling and boosting
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Efficient stepwise selection in decomposable models
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Bayesian class-matched multinet classifier
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Bayesian learning of markov network structure
ECML'06 Proceedings of the 17th European conference on Machine Learning
Bayesian learning with mixtures of trees
ECML'06 Proceedings of the 17th European conference on Machine Learning
Mixtures of kikuchi approximations
ECML'06 Proceedings of the 17th European conference on Machine Learning
Probability approximation using best-tree distribution for skin detection
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Learning Bayesian network classifiers by risk minimization
International Journal of Approximate Reasoning
Robust bayesian linear classifier ensembles
ECML'05 Proceedings of the 16th European conference on Machine Learning
A New Bayesian Tree Learning Method with Reduced Time and Space Complexity
Fundamenta Informaticae
Selectivity estimation for hybrid queries over text-rich data graphs
Proceedings of the 16th International Conference on Extending Database Technology
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This paper describes the mixtures-of-trees model, a probabilistic model for discrete multidimensional domains. Mixtures-of-trees generalize the probabilistic trees of Chow and Liu (1968) in a different and complementary direction to that of Bayesian networks. We present efficient algorithms for learning mixtures-of-trees models in maximum likelihood and Bayesian frameworks. We also discuss additional efficiencies that can be obtained when data are "sparse," and we present data structures and algorithms that exploit such sparseness. Experimental results demonstrate the performance of the model for both density estimation and classification. We also discuss the sense in which tree-based classifiers perform an implicit form of feature selection, and demonstrate a resulting insensitivity to irrelevant attributes.