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ML
2008
ACM
222views Machine Learning» more  ML 2008»
13 years 7 months ago
Boosted Bayesian network classifiers
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
TIP
2008
185views more  TIP 2008»
13 years 7 months ago
Active Learning Methods for Interactive Image Retrieval
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
Philippe Henri Gosselin, Matthieu Cord
ICCV
2003
IEEE
14 years 9 months ago
Boosting Chain Learning for Object Detection
A general classification framework, called boosting chain, is proposed for learning boosting cascade. In this framework, a "chain" structure is introduced to integrate h...
Rong Xiao, Long Zhu, HongJiang Zhang
CVPR
2008
IEEE
13 years 7 months ago
Joint learning and dictionary construction for pattern recognition
We propose a joint representation and classification framework that achieves the dual goal of finding the most discriminative sparse overcomplete encoding and optimal classifier p...
Duc-Son Pham, Svetha Venkatesh
CEC
2010
IEEE
13 years 8 months ago
Multi-objective memetic evolution of ART-based classifiers
In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...