Natural gradient works efficiently in learning
Neural Computation
An Introduction to Variational Methods for Graphical Models
Machine Learning
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
Integrating Declarative Knowledge in Hierarchical Clustering Tasks
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
On-Line Handwriting Recognition with Support Vector Machines " A Kernel Approach
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
The Journal of Machine Learning Research
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Solving large scale linear prediction problems using stochastic gradient descent algorithms
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Simultaneous Feature Selection and Clustering Using Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Dimension Reduction in Text Classification with Support Vector Machines
The Journal of Machine Learning Research
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Spatial Priors for Part-Based Recognition Using Statistical Models
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Object Class Recognition Using Multiple Layer Boosting with Heterogeneous Features
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Sparse Texture Representation Using Local Affine Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Maximum Entropy Framework for Part-Based Texture and Object Recognition
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Pattern Recognition Letters - Special issue: Artificial neural networks in pattern recognition
Online Model Selection Based on the Variational Bayes
Neural Computation
A Visual Vocabulary for Flower Classification
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Computer Vision and Image Understanding
The Journal of Machine Learning Research
Learning from Data: Concepts, Theory, and Methods
Learning from Data: Concepts, Theory, and Methods
Pattern Analysis & Applications
A Hybrid Feature Extraction Selection Approach for High-Dimensional Non-Gaussian Data Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online clustering via finite mixtures of Dirichlet and minimum message length
Engineering Applications of Artificial Intelligence
A Dirichlet process mixture of generalized Dirichlet distributions for proportional data modeling
IEEE Transactions on Neural Networks
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Possibilistic Clustering Based on Robust Modeling of Finite Generalized Dirichlet Mixture
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Bayesian Estimation of Beta Mixture Models with Variational Inference
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
IEEE Transactions on Image Processing
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Three frequently recurring themes in machine learning, data mining and related disciplines are clustering, feature selection and online learning. Motivated by the importance of these themes which are generally interrelated, we propose a statistical framework for simultaneous online clustering and feature selection using finite generalized Dirichlet mixture model. The proposed framework allows to control overfitting by, dynamically and simultaneously, adjusting the mixture model's parameters, number of components and the features weights. We describe a principled variational approach for learning the parameters of the proposed statistical model. Results on both synthetic data and real applications involving online documents and images clustering show the merits of the proposed approach.