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ICANN
2007
Springer
14 years 3 months ago
Incremental and Decremental Learning for Linear Support Vector Machines
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Enrique Romero, Ignacio Barrio, Lluís Belan...
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
14 years 9 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ESANN
2007
13 years 10 months ago
Interval discriminant analysis using support vector machines
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Cecilio Angulo, Davide Anguita, Luis Gonzál...
FGR
2006
IEEE
297views Biometrics» more  FGR 2006»
14 years 3 months ago
Automatic Skin Segmentation for Gesture Recognition Combining Region and Support Vector Machine Active Learning
Skin segmentation is the cornerstone of many applications such as gesture recognition, face detection, and objectionable image filtering. In this paper, we attempt to address the ...
Junwei Han, George Awad, Alistair Sutherland, Hai ...
IJCNN
2006
IEEE
14 years 3 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li