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» Graph Mining based on a Data Partitioning Approach
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JMLR
2012
13 years 2 months ago
Globally Optimizing Graph Partitioning Problems Using Message Passing
Graph partitioning algorithms play a central role in data analysis and machine learning. Most useful graph partitioning criteria correspond to optimizing a ratio between the cut a...
Elad Mezuman, Yair Weiss
116
Voted
PKDD
2009
Springer
184views Data Mining» more  PKDD 2009»
15 years 7 months ago
Learning Preferences with Hidden Common Cause Relations
Abstract. Gaussian processes have successfully been used to learn preferences among entities as they provide nonparametric Bayesian approaches for model selection and probabilistic...
Kristian Kersting, Zhao Xu
92
Voted
SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
15 years 1 months ago
Fast Multilevel Transduction on Graphs
The recent years have witnessed a surge of interest in graphbased semi-supervised learning methods. The common denominator of these methods is that the data are represented by the...
Fei Wang, Changshui Zhang
139
Voted
DAWAK
2005
Springer
15 years 6 months ago
Nearest Neighbor Search on Vertically Partitioned High-Dimensional Data
Abstract. In this paper, we present a new approach to indexing multidimensional data that is particularly suitable for the efficient incremental processing of nearest neighbor quer...
Evangelos Dellis, Bernhard Seeger, Akrivi Vlachou
ICDE
1998
IEEE
108views Database» more  ICDE 1998»
16 years 1 months ago
Efficient Discovery of Functional and Approximate Dependencies Using Partitions
Discovery of functionaldependencies from relations has been identified as an important database analysis technique. In this paper, we present a new approach for finding functional...
Ykä Huhtala, Juha Kärkkäinen, Pasi ...