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123
Voted
ICML
2004
IEEE
16 years 3 months ago
2004
IEEE
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
113
Voted
PKDD
2009
Springer
15 years 9 months ago
2009
Springer
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
123
Voted
ICIP
2002
IEEE
16 years 4 months ago
2002
IEEE
In this work, we explore the use of a learning-based framework for retrieval of relevant mammogram images from a database, for purposes of aiding diagnoses. A fundamental issue is...
115
Voted
NECO
2008
15 years 2 months ago
2008
Iterative learning algorithms that approximate the solution of support vector machines (SVMs) have two potential advantages. First, they allow for online and active learning. Seco...
116
Voted
AIPRF
2007
15 years 4 months ago
2007
In this paper, we implemented very simple plan generator which can help the novice researchers do their research efficiently. We have assumed that we should not make domain expert...