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ICML
2003
IEEE
14 years 7 months ago
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
Aldebaro Klautau, Nikola Jevtic, Alon Orlitsky
CVPR
2007
IEEE
14 years 9 months ago
Online Learning Asymmetric Boosted Classifiers for Object Detection
We present an integrated framework for learning asymmetric boosted classifiers and online learning to address the problem of online learning asymmetric boosted classifiers, which ...
Minh-Tri Pham, Tat-Jen Cham
ICPR
2010
IEEE
13 years 11 months ago
Evolving Fuzzy Classifiers: Application to Incremental Learning of Handwritten Gesture Recognition Systems
In this paper, we present a new method to design customizable self-evolving fuzzy rule-based classifiers. The presented approach combines an incremental clustering algorithm with a...
Abdullah Almaksour, Eric Anquetil, Solen Quiniou, ...
JCP
2006
78views more  JCP 2006»
13 years 7 months ago
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning
Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to le...
Ling Zhuang, Honghua Dai
MCS
2005
Springer
14 years 17 days ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...