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DATAMINE
2006
166views more  DATAMINE 2006»
15 years 6 months ago
Accelerated EM-based clustering of large data sets
Motivated by the poor performance (linear complexity) of the EM algorithm in clustering large data sets, and inspired by the successful accelerated versions of related algorithms l...
Jakob J. Verbeek, Jan Nunnink, Nikos A. Vlassis
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IJSTM
2008
77views more  IJSTM 2008»
15 years 6 months ago
The internal differentiation of the KIBS sector: empirical evidence from cluster analysis
: The sector of Knowledge-Intensive Business Services (KIBS) is characterised by high rates of firm fluctuation, rapid changes in technological progress (e.g., in the software indu...
Daniel Horgos, Andreas Koch
TASLP
2008
120views more  TASLP 2008»
15 years 5 months ago
Rapid Speaker Adaptation Using Clustered Maximum-Likelihood Linear Basis With Sparse Training Data
Abstract-- Speaker space based adaptation methods for automatic speech recognition have been shown to provide significant performance improvements for tasks where only a few second...
Yun Tang, Richard Rose
TCAD
2008
116views more  TCAD 2008»
15 years 5 months ago
Scalable Synthesis and Clustering Techniques Using Decision Diagrams
BDDs have proven to be an efficient means to represent and manipulate Boolean formulae [1] and sets [2] due to their compactness and canonicality. In this work, we leverage the eff...
Andrew C. Ling, Jianwen Zhu, Stephen Dean Brown
IS
2007
15 years 5 months ago
Mining association rules in very large clustered domains
Emerging applications introduce the requirement for novel association-rule mining algorithms that will be scalable not only with respect to the number of records (number of rows) ...
Alexandros Nanopoulos, Apostolos N. Papadopoulos, ...