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ICANN
2009
Springer
13 years 5 months ago
MINLIP: Efficient Learning of Transformation Models
Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
INCDM
2010
Springer
308views Data Mining» more  INCDM 2010»
13 years 9 months ago
Data Mining with Neural Networks and Support Vector Machines Using the R/rminer Tool
We present rminer, our open source library for the R tool that facilitates the use of data mining (DM) algorithms, such as neural Networks (NNs) and support vector machines (SVMs),...
Paulo Cortez
ESANN
2000
13 years 9 months ago
Algorithmic approaches to training Support Vector Machines: a survey
: Support Vector Machines (SVMs) have become an increasingly popular tool for machine learning tasks involving classi cation, regression or novelty detection. They exhibit good gen...
Colin Campbell
NIPS
1996
13 years 9 months ago
Improving the Accuracy and Speed of Support Vector Machines
Support Vector Learning Machines (SVM) are nding application in pattern recognition, regression estimation, and operator inversion for ill-posed problems. Against this very genera...
Christopher J. C. Burges, Bernhard Schölkopf
IJON
2006
119views more  IJON 2006»
13 years 7 months ago
Support vector machine for functional data classification
Abstract. Functional data analysis is a growing research field and numerous works present a generalization of the classical statistical methods to function classification or regres...
Fabrice Rossi, Nathalie Villa