Robust Bayesian clustering

A new variational Bayesian learning algorithm for Student- t mixture models is introduced. This algorithm leads to (i) robust density estimation, (ii) robust clustering and (iii) robust automatic model selection. Gaussian mixture models are learning machines which are based on a divide-and-conquer a...

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Veröffentlicht in:	Neural networks 2007, Vol.20 (1), p.129-138
Hauptverfasser:	Archambeau, Cédric, Verleysen, Michel
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Approximate inference Artificial intelligence Bayes Theorem Bayesian learning Cluster Analysis Clustering Computer science control theory systems Connectionism. Neural networks Density estimation Exact sciences and technology Graphical models Humans Information, signal and communications theory Learning Learning and adaptive systems Mixture models Model selection Normal Distribution Robotics Robustness to outliers Signal and communications theory Signal representation. Spectral analysis Signal, noise Student- [formula omitted] distribution Telecommunications and information theory Variational inference
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