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JMLR
2010
152views more  JMLR 2010»
14 years 8 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...

Book
778views
16 years 11 months ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
ISNN
2007
Springer
15 years 7 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
CIKM
2005
Springer
15 years 7 months ago
Information retrieval and machine learning for probabilistic schema matching
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas e.g. in the data exchange domain, or for distribute...
Henrik Nottelmann, Umberto Straccia
MMS
2006
15 years 1 months ago
Support vector machine active learning for music retrieval
Searching and organizing growing digital music collections requires a computational model of music similarity. This paper describes a system for performing flexible music similarit...
Michael I. Mandel, Graham E. Poliner, Daniel P. W....