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KDD
2007
ACM
190views Data Mining» more  KDD 2007»
16 years 7 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 7 months ago
Outlier detection by sampling with accuracy guarantees
An effective approach to detect anomalous points in a data set is distance-based outlier detection. This paper describes a simple sampling algorithm to efficiently detect distance...
Mingxi Wu, Chris Jermaine
KDD
2006
ACM
118views Data Mining» more  KDD 2006»
16 years 7 months ago
Reducing the human overhead in text categorization
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
Arnd Christian König, Eric Brill
KDD
2006
ACM
163views Data Mining» more  KDD 2006»
16 years 7 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 7 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney
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