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SIGMOD
2000
ACM
212views Database» more  SIGMOD 2000»
14 years 1 days ago
SQLEM: Fast Clustering in SQL using the EM Algorithm
Clustering is one of the most important tasks performed in Data Mining applications. This paper presents an e cient SQL implementation of the EM algorithm to perform clustering in...
Carlos Ordonez, Paul Cereghini
KAIS
2006
164views more  KAIS 2006»
13 years 7 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 2 months ago
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Kanishka Bhaduri, Ashok N. Srivastava
CIVR
2009
Springer
583views Image Analysis» more  CIVR 2009»
14 years 7 months ago
Mining from Large Image Sets
So far, most image mining was based on interactive querying. Although such querying will remain important in the future, several applications need image mining at such wide scale...
Luc J. Van Gool, Michael D. Breitenstein, Stephan ...
TSP
2008
167views more  TSP 2008»
13 years 6 months ago
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
Kai Ni, John William Paisley, Lawrence Carin, Davi...