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PAKDD
2009
ACM
115views Data Mining» more  PAKDD 2009»
13 years 11 months ago
Data Mining for Intrusion Detection: From Outliers to True Intrusions
Data mining for intrusion detection can be divided into several sub-topics, among which unsupervised clustering has controversial properties. Unsupervised clustering for intrusion...
Goverdhan Singh, Florent Masseglia, Céline ...
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
14 years 4 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
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 5 months ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
ICPR
2002
IEEE
14 years 5 months ago
Probabilistic Models for Generating, Modelling and Matching Image Categories
In this paper we present a probabilistic and continuous framework for supervised image category modelling and matching as well as unsupervised clustering of image space into image...
Hayit Greenspan, Shiri Gordon, Jacob Goldberger
CVPR
1998
IEEE
14 years 6 months ago
Clustering Appearances of 3D Objects
We introduce a method for unsupervised clustering of images of 3D objects. Our method examines the space of all images and partitions the images into sets that form smooth and par...
Ronen Basri, Dan Roth, David W. Jacobs