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NIPS
2000
15 years 7 months ago
Incremental and Decremental Support Vector Machine Learning
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
Gert Cauwenberghs, Tomaso Poggio
JMLR
2002
73views more  JMLR 2002»
15 years 6 months ago
Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components
We apply a variational method to automatically determine the number of mixtures of independent components in high-dimensional datasets, in which the sources may be nonsymmetricall...
Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 6 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
GRC
2010
IEEE
15 years 7 months ago
Learning Multiple Latent Variables with Self-Organizing Maps
Inference of latent variables from complicated data is one important problem in data mining. The high dimensionality and high complexity of real world data often make accurate infe...
Lili Zhang, Erzsébet Merényi
CVPR
2011
IEEE
15 years 2 months ago
Scalable Multi-class Object Detection
Scalability of object detectors with respect to the number of classes is a very important issue for applications where many object classes need to be detected. While combining sin...
Nima Razavi, Juergen Gall, Luc VanGool