2037 search results - page 100 / 408 » Chunking with Support Vector Machines |
143
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ICML
2001
IEEE
16 years 7 months ago
2001
IEEE
In this paper, we propose a unified non-quadratic loss function for regression known as soft insensitive loss function (SILF). SILF is a flexible model and possesses most of the d...
177
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IJCNN
2000
IEEE
15 years 10 months ago
2000
IEEE
In the Support Vector Machines (SVM) framework, the positive-definite kernel can be seen as representing a fixed similarity measure between two patterns, and a discriminant func...
155
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ICML
2000
IEEE
16 years 7 months ago
2000
IEEE
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...
159
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MICCAI
2006
Springer
16 years 7 months ago
2006
Springer
Abstract. The support vector domain description is a one-class classification method that estimates the shape and extent of the distribution of a data set. This separates the data ...
178
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ICML
2004
IEEE
16 years 7 months ago
2004
IEEE
Multi-view algorithms, such as co-training and co-EM, utilize unlabeled data when the available attributes can be split into independent and compatible subsets. Co-EM outperforms ...