Algorithms for clustering data
Algorithms for clustering data
A deterministic annealing approach to clustering
Pattern Recognition Letters
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Pattern Recognition
Bayesian radial basis functions of variable dimension
Neural Computation
Bayesian Approaches to Gaussian Mixture Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Variational mixture of Bayesian independent component analyzers
Neural Computation
Hierarchical Shape Modeling for Automatic Face Localization
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
A Novel Approach to Generate Multiple Shape Models for Tracking Applications
AMDO '02 Proceedings of the Second International Workshop on Articulated Motion and Deformable Objects
Unsupervised Parameterisation of Gaussian Mixture Models
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Hierarchy, priors and wavelets: structure and signal modelling using ICA
Signal Processing - Special issue on independent components analysis and beyond
Semisupervised Learning of Hierarchical Latent Trait Models for Data Visualization
IEEE Transactions on Knowledge and Data Engineering
The minimum-entropy set cover problem
Theoretical Computer Science - Automata, languages and programming: Algorithms and complexity (ICALP-A 2004)
A New Cluster Validity for Data Clustering
Neural Processing Letters
A robust deterministic annealing algorithm for data clustering
Data & Knowledge Engineering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian inference on principal component analysis using reversible jump Markov chain Monte Carlo
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
On similarities between inference in game theory and machine learning
Journal of Artificial Intelligence Research
Generalized competitive learning of Gaussian mixture models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Active curve axis Gaussian mixture models
Pattern Recognition
Maximum within-cluster association
Pattern Recognition Letters
Gaussian mixture learning via robust competitive agglomeration
Pattern Recognition Letters
Feature subset-wise mixture model-based clustering via local search algorithm
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
| Hi-index | 0.14 |
Problems in data analysis often require the unsupervised partitioning of a data set into classes. Several methods exist for such partitioning but many have the weakness of being formulated via strict parametric models (e.g., each class is modeled by a single Gaussian) or being computationally intensive in high-dimensional data spaces. We reconsider the notion of such cluster analysis in information-theoretic terms and show that an efficient partitioning may be given via a minimization of partition entropy. A reversible-jump sampling is introduced to explore the variable-dimension space of partition models.