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ICML
2010
IEEE
15 years 7 months ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
ICML
2010
IEEE
15 years 7 months ago
The Elastic Embedding Algorithm for Dimensionality Reduction
We propose a new dimensionality reduction method, the elastic embedding (EE), that optimises an intuitive, nonlinear objective function of the low-dimensional coordinates of the d...
Miguel Á. Carreira-Perpiñán
ML
2000
ACM
144views Machine Learning» more  ML 2000»
15 years 6 months ago
MultiBoosting: A Technique for Combining Boosting and Wagging
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees. MultiBoosting can be viewed as combining AdaBoost with wagging. It is abl...
Geoffrey I. Webb
ML
2002
ACM
146views Machine Learning» more  ML 2002»
15 years 6 months ago
Kernel Matching Pursuit
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
Pascal Vincent, Yoshua Bengio
JMLR
2012
13 years 9 months ago
Perturbation based Large Margin Approach for Ranking
We consider the task of devising large-margin based surrogate losses for the learning to rank problem. In this learning to rank setting, the traditional hinge loss for structured ...
Eunho Yang, Ambuj Tewari, Pradeep D. Ravikumar