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» Normalization in Support Vector Machines
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ICML
2005
IEEE
16 years 5 months ago
Object correspondence as a machine learning problem
We propose machine learning methods for the estimation of deformation fields that transform two given objects into each other, thereby establishing a dense point to point correspo...
Bernhard Schölkopf, Florian Steinke, Volker B...
JMLR
2012
13 years 7 months ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
IJCNN
2007
IEEE
15 years 10 months ago
Generalised Kernel Machines
Abstract— The generalised linear model (GLM) is the standard approach in classical statistics for regression tasks where it is appropriate to measure the data misfit using a lik...
Gavin C. Cawley, Gareth J. Janacek, Nicola L. C. T...
ICANN
2007
Springer
15 years 10 months ago
Selection of Basis Functions Guided by the L2 Soft Margin
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Ignacio Barrio, Enrique Romero, Lluís Belan...
MIAR
2010
IEEE
15 years 2 months ago
Skin Lesions Classification with Optical Spectroscopy
Diagnosis of benign and malign skin lesions is currently mostly relying on visual assessment and frequent biopsies performed by dermatologists. As the timely and correct diagnosis ...
Asad Safi, Victor Castaneda, Tobias Lasser, Nassir...