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ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
15 years 4 months ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....
MLDM
2007
Springer
15 years 4 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
IBPRIA
2005
Springer
15 years 3 months ago
An Approach to Vision-Based Person Detection in Robotic Applications
We present an approach to vision-based person detection in robotic applications that integrates top down template matching with bottom up classifiers. We detect components of the ...
Carlos D. Castillo, Carolina Chang
JMLR
2011
110views more  JMLR 2011»
14 years 4 months ago
Training SVMs Without Offset
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Ingo Steinwart, Don R. Hush, Clint Scovel
CIARP
2010
Springer
14 years 7 months ago
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls
Abstract. It has been shown that many kernel methods can be equivalently formulated as minimal-enclosing-ball (MEB) problems in certain feature space. Exploiting this reduction eff...
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lod...