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PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 10 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...
SAC
2009
ACM
16 years 1 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
CSDA
2006
98views more  CSDA 2006»
15 years 6 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
SIGIR
2002
ACM
15 years 6 months ago
Unsupervised document classification using sequential information maximization
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
Noam Slonim, Nir Friedman, Naftali Tishby
IJCM
2007
205views more  IJCM 2007»
15 years 6 months ago
BTF modelling using BRDF texels
The highest fidelity representations of realistic real-world materials currently used comprise Bidirectional Texture Functions (BTF). The BTF is a six dimensional function dependi...
Jirí Filip, Michal Haindl