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COLT
1999
Springer
15 years 11 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...
ICML
2007
IEEE
16 years 7 months ago
Multiclass core vector machine
Even though several techniques have been proposed in the literature for achieving multiclass classification using Support Vector Machine(SVM), the scalability aspect of these appr...
S. Asharaf, M. Narasimha Murty, Shirish Krishnaj S...
ALT
2000
Springer
15 years 10 months ago
Computationally Efficient Transductive Machines
In this paper1 we propose a new algorithm for providing confidence and credibility values for predictions on a multi-class pattern recognition problem which uses Support Vector mac...
Craig Saunders, Alexander Gammerman, Volodya Vovk
GECCO
2007
Springer
148views Optimization» more  GECCO 2007»
16 years 28 days ago
Fuzzy-UCS: preliminary results
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. Fuzzy-UCS combines the generalization capabilities of UCS...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
ICMLA
2009
15 years 4 months ago
Knowledge Transfer for Feature Generation in Document Classification
One important problem in machine learning is how to extract knowledge from prior experience, then transfer and apply this knowledge in new learning tasks. To address this problem, ...
Jian Zhang, Shobhit S. Shakya