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» New approaches to support vector ordinal regression
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GLOBECOM
2008
IEEE
15 years 6 months ago
Distributed Regression in Sensor Networks with a Reduced-Order Kernel Model
Abstract—Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena, such as the temperature field in a given region. Appl...
Paul Honeine, Mehdi Essoloh, Cédric Richard...
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
15 years 9 months ago
Hierarchical Linear Discriminant Analysis for Beamforming.
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Barry L. Drake, Haesun Park, Jaegul Choo
NN
2008
Springer
158views Neural Networks» more  NN 2008»
14 years 11 months ago
Improved mapping of information distribution across the cortical surface with the support vector machine
The early visual cortices represent information of several stimulus attributes, such as orientation and color. To understand the coding mechanisms of these attributes in the brain...
Youping Xiao, Ravi Rao, Guillermo A. Cecchi, Ehud ...
ICDM
2002
IEEE
133views Data Mining» more  ICDM 2002»
15 years 4 months ago
Learning with Progressive Transductive Support Vector Machine
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Yisong Chen, Guoping Wang, Shihai Dong
AIA
2007
15 years 1 months ago
Improving the aggregating algorithm for regression
Kernel Ridge Regression (KRR) and the recently developed Kernel Aggregating Algorithm for Regression (KAAR) are regression methods based on Least Squares. KAAR has theoretical adv...
Steven Busuttil, Yuri Kalnishkan, Alexander Gammer...