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129
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ESANN
2006
15 years 5 months ago
Unsupervised clustering of continuous trajectories of kinematic trees with SOM-SD
We explore the capability of the Self Organizing Map for structured data (SOM-SD) to compress continuous time data recorded from a kinematic tree, which can represent a robot or an...
Jochen J. Steil, Risto Koiva, Alessandro Sperduti
DKE
2006
67views more  DKE 2006»
15 years 3 months ago
Indexed-based density biased sampling for clustering applications
Density biased sampling (DBS) has been proposed to address the limitations of Uniform sampling, by producing the desired probability distribution in the sample. The ease of produc...
Alexandros Nanopoulos, Yannis Theodoridis, Yannis ...
105
Voted
SAC
2009
ACM
15 years 10 months ago
Parameterless outlier detection in data streams
Outlyingness is a subjective concept relying on the isolation level of a (set of) record(s). Clustering-based outlier detection is a field that aims to cluster data and to detect...
Alice Marascu, Florent Masseglia
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
15 years 8 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. ...
CSDA
2006
98views more  CSDA 2006»
15 years 3 months ago
Fast estimation algorithm for likelihood-based analysis of repeated categorical responses
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
Jukka Jokinen