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116
Voted
PKDD
2009
Springer
15 years 10 months ago
2009
Springer
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an e...
107
Voted
ICDM
2008
IEEE
15 years 10 months ago
2008
IEEE
Semi-supervised classification methods aim to exploit labelled and unlabelled examples to train a predictive model. Most of these approaches make assumptions on the distribution ...
115
Voted
PKDD
2010
Springer
15 years 2 months ago
2010
Springer
Abstract. We present an automated tool with a web interface for tracking the prevalence of Influenza-like Illness (ILI) in several regions of the United Kingdom using the contents...
145
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SDM
2012
SIAM
13 years 6 months ago
2012
SIAM
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampl...
170
Voted
KDD
2003
ACM
16 years 4 months ago
2003
ACM
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...