CORR
2010
Springer
13 years 4 months ago
2010
Springer
This paper studies the outlier detection problem from the point of view of penalized regressions. Our regression model adds one mean shift parameter for each of the n data points....
NC
1998
13 years 6 months ago
1998
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...
IMAGING
2003
13 years 6 months ago
2003
Computer vision applications are able to model and reconstruct three dimensional scenes from several pictures. In this work, we are interested in the group of algorithm that regis...
EUSFLAT
2003
13 years 6 months ago
2003
In regression analysis, outliers always represent difficulties because they cause modeling errors. But under certain circumstances, they can actually contain useful information, as...
ICMLA
2004
13 years 6 months ago
2004
Detecting outliers is an important topic in data mining. Sometimes the outliers are more interesting than the rest of the data. Outlier identification has lots of applications, su...
LREC
2010
13 years 6 months ago
2010
This paper proposes the method to detect peculiar examples of the target word from a corpus. The peculiar example is regarded as an outlier in the given example set. Therefore we ...
SIGMOD
2000
ACM
13 years 9 months ago
2000
ACM
For many KDD applications, such as detecting criminal activities in E-commerce, finding the rare instances or the outliers, can be more interesting than finding the common pattern...
ICDM
2002
IEEE
13 years 9 months ago
2002
IEEE
We have proposed replicator neural networks (RNNs) as an outlier detecting algorithm [15]. Here we compare RNN for outlier detection with three other methods using both publicly a...
ASP
2003
Springer
13 years 10 months ago
2003
Springer
Default logic is used to describe regular behavior and normal properties. We suggest to exploit the framework of default logic for detecting outliers - individuals who behave in a...
ICDAR
2003
IEEE
13 years 10 months ago
2003
IEEE
A class-modular generalized learning vector quantization (GLVQ) ensemble method with outlier learning for handwritten digit recognition is proposed. A GLVQ classifier is one of d...