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TNN
2008
129views more  TNN 2008»
15 years 5 months ago
Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point
In this paper, a new kernel-based method for data visualization and dimensionality reduction is proposed. A reference point is considered corresponding to additional constraints ta...
Johan A. K. Suykens
ICML
2002
IEEE
16 years 6 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
BMCBI
2004
113views more  BMCBI 2004»
15 years 5 months ago
Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
CLUSTER
2006
IEEE
15 years 11 months ago
Kernel-Level Measurement for Integrated Parallel Performance Views: the KTAU Project
The effect of the operating system on application performance is an increasingly important consideration in high performance computing. OS kernel measurement is key to understandi...
Aroon Nataraj, Allen D. Malony, Sameer Shende, Ala...
JC
2011
87views more  JC 2011»
15 years 15 days ago
Lower bounds for the complexity of linear functionals in the randomized setting
Abstract. Hinrichs [3] recently studied multivariate integration defined over reproducing kernel Hilbert spaces in the randomized setting and for the normalized error criterion. I...
Erich Novak, Henryk Wozniakowski