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» Approximation Algorithms for Tensor Clustering
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KAIS
2006
110views more  KAIS 2006»
13 years 7 months ago
Multi-step density-based clustering
Abstract. Data mining in large databases of complex objects from scientific, engineering or multimedia applications is getting more and more important. In many areas, complex dista...
Stefan Brecheisen, Hans-Peter Kriegel, Martin Pfei...
GECCO
2005
Springer
144views Optimization» more  GECCO 2005»
14 years 1 months ago
Multiobjective hBOA, clustering, and scalability
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Martin Pelikan, Kumara Sastry, David E. Goldberg
SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
13 years 9 months ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee
KDD
1997
ACM
159views Data Mining» more  KDD 1997»
13 years 11 months ago
New Algorithms for Fast Discovery of Association Rules
Discovery of association rules is an important problem in database mining. In this paper we present new algorithms for fast association mining, which scan the database only once, ...
Mohammed Javeed Zaki, Srinivasan Parthasarathy, Mi...
KDD
2000
ACM
149views Data Mining» more  KDD 2000»
13 years 11 months ago
Efficient clustering of high-dimensional data sets with application to reference matching
Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
Andrew McCallum, Kamal Nigam, Lyle H. Ungar