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» A Statistical Clustering Model and Algorithm
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JMLR
2010
129views more  JMLR 2010»
15 years 1 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
ICDM
2008
IEEE
142views Data Mining» more  ICDM 2008»
16 years 1 months ago
Clustering Events on Streams Using Complex Context Information
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an adminis...
YongChul Kwon, Wing Yee Lee, Magdalena Balazinska,...
ADBIS
2006
Springer
166views Database» more  ADBIS 2006»
16 years 18 days ago
Clustering-Based Materialized View Selection in Data Warehouses
materialized view selection is a non-trivial task. Hence, its complexity must be reduced. A judicious choice of views must be costdriven and influenced by the workload experienced...
Kamel Aouiche, Pierre-Emmanuel Jouve, Jér&o...
CHES
2009
Springer
157views Cryptology» more  CHES 2009»
16 years 7 months ago
Differential Cluster Analysis
Abstract. We propose a new technique called Differential Cluster Analysis for side-channel key recovery attacks. This technique uses cluster analysis to detect internal collisions ...
Lejla Batina, Benedikt Gierlichs, Kerstin Lemke-Ru...
ICANN
2003
Springer
15 years 11 months ago
Expectation-MiniMax Approach to Clustering Analysis
Abstract. This paper proposes a general approach named ExpectationMiniMax (EMM) for clustering analysis without knowing the cluster number. It describes the contrast function of Ex...
Yiu-ming Cheung