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BIOID
2008
103views Biometrics» more  BIOID 2008»
13 years 11 months ago
Promoting Diversity in Gaussian Mixture Ensembles: An Application to Signature Verification
Abstract. Classifiers based on Gaussian mixture models are good performers in many pattern recognition tasks. Unlike decision trees, they can be described as stable classifier: a s...
Jonas Richiardi, Andrzej Drygajlo, Laetitia Todesc...
IDA
2007
Springer
13 years 9 months ago
In search of deterministic methods for initializing K-means and Gaussian mixture clustering
The performance of K-means and Gaussian mixture model (GMM) clustering depends on the initial guess of partitions. Typically, clus∗ corresponding author 1
Ting Su, Jennifer G. Dy
TIP
2002
179views more  TIP 2002»
13 years 9 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
ICC
2007
IEEE
14 years 4 months ago
A Low-Complexity Impulse Radio Receiver based upon Gaussian Mixtures
Abstract— Ultra wide band (UWB) impulse radio (IR) technology calls for robust and low-complexity receiver techniques. State-of-the-art proposals are both coherent ML receivers, ...
Tomaso Erseghe
JAIR
1998
198views more  JAIR 1998»
13 years 9 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...