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149
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ICML
2007
IEEE
16 years 5 months ago
Classifying matrices with a spectral regularization
We propose a method for the classification of matrices. We use a linear classifier with a novel regularization scheme based on the spectral 1-norm of its coefficient matrix. The s...
Ryota Tomioka, Kazuyuki Aihara
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 5 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
147
Voted
INFORMS
2010
177views more  INFORMS 2010»
15 years 3 months ago
Binarized Support Vector Machines
The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have bec...
Emilio Carrizosa, Belen Martin-Barragan, Dolores R...
CLEF
2010
Springer
15 years 5 months ago
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees
Abstract. In this paper, we present a multiple targets classification system for visual concepts detection and image annotation. Multiple targets classification (MTC) is a variant ...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 5 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims