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» Learning to learn with the informative vector machine
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ICML
2000
IEEE
16 years 2 months ago
Bounds on the Generalization Performance of Kernel Machine Ensembles
We study the problem of learning using combinations of machines. In particular we present new theoretical bounds on the generalization performance of voting ensembles of kernel ma...
Luis Pérez-Breva, Massimiliano Pontil, Theo...
ICIP
2003
IEEE
16 years 3 months ago
Histogram intersection kernel for image classification
In this paper we address the problem of classifying images, by exploiting global features that describe color and illumination properties, and by using the statistical learning pa...
Annalisa Barla, Francesca Odone, Alessandro Verri
ICML
2001
IEEE
16 years 2 months ago
Learning with the Set Covering Machine
We generalize the classical algorithms of Valiant and Haussler for learning conjunctions and disjunctions of Boolean attributes to the problem of learning these functions over arb...
Mario Marchand, John Shawe-Taylor
BMCBI
2006
151views more  BMCBI 2006»
15 years 2 months ago
Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues
Background: Word sense disambiguation (WSD) is critical in the biomedical domain for improving the precision of natural language processing (NLP), text mining, and information ret...
Hua Xu, Marianthi Markatou, Rositsa Dimova, Hongfa...
PAKDD
2011
ACM
253views Data Mining» more  PAKDD 2011»
14 years 4 months ago
Balance Support Vector Machines Locally Using the Structural Similarity Kernel
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
Jianxin Wu