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ICMLA
2009
14 years 7 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
ICMLA
2010
14 years 7 months ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz
MICAI
2004
Springer
15 years 2 months ago
An Optimization Algorithm Based on Active and Instance-Based Learning
We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
Olac Fuentes, Thamar Solorio
JCP
2006
78views more  JCP 2006»
14 years 9 months ago
Parameter Optimization of Kernel-based One-class Classifier on Imbalance Learning
Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to le...
Ling Zhuang, Honghua Dai
ICML
2005
IEEE
15 years 10 months ago
A support vector method for multivariate performance measures
This paper presents a Support Vector Method for optimizing multivariate nonlinear performance measures like the F1score. Taking a multivariate prediction approach, we give an algo...
Thorsten Joachims