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» Finding Metric Structure in Information Theoretic Clustering
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EH
2004
IEEE
74views Hardware» more  EH 2004»
15 years 10 months ago
Sensory Channel Grouping and Structure from Uninterpreted Sensor Data
In this paper we focus on the problem of making a model of the sensory apparatus from raw uninterpreted sensory data as defined by Pierce and Kuipers (Artificial Intelligence 92:1...
Lars Olsson, Chrystopher L. Nehaniv, Daniel Polani
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 7 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
DAWAK
2006
Springer
15 years 10 months ago
Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
Abstract. Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view ...
Jiuyong Li, Raymond Chi-Wing Wong, Ada Wai-Chee Fu...
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 11 months ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
BMVC
2010
15 years 4 months ago
Manifold Learning for Multi-Modal Image Registration
The standard approach to multi-modal registration is to apply sophisticated similarity metrics such as mutual information. The disadvantage of these measures, in contrast to simpl...
Christian Wachinger, Nassir Navab