TMI
2002
13 years 4 months ago
2002
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
TIT
2002
13 years 4 months ago
2002
Generalization bounds depending on the margin of a classifier are a relatively recent development. They provide an explanation of the performance of state-of-the-art learning syste...
ML
2002
ACM
13 years 4 months ago
2002
ACM
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequenc...
ML
2002
ACM
13 years 4 months ago
2002
ACM
The decomposition method is currently one of the major methods for solving support vector machines. An important issue of this method is the selection of working sets. In this pape...
ML
2002
ACM
13 years 4 months ago
2002
ACM
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated...
JMLR
2002
13 years 4 months ago
2002
When constructing a classifier, the probability of correct classification of future data points should be maximized. We consider a binary classification problem where the mean and...
SIGKDD
2000
13 years 4 months ago
2000
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
JCB
2000
13 years 4 months ago
2000
A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support...
IJCV
2000
13 years 4 months ago
2000
In this paper we first overview the main concepts of Statistical Learning Theory, a framework in which learning from examples can be studied in a principled way. We then briefly di...
COLING
2002
13 years 4 months ago
2002
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...