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KDD
2004
ACM
190views Data Mining» more  KDD 2004»
15 years 10 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
PREMI
2005
Springer
15 years 3 months ago
Towards Generic Pattern Mining
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Template...
Mohammed Javeed Zaki, Nilanjana De, Feng Gao, Nage...
GBRPR
2003
Springer
15 years 2 months ago
Constructing Stochastic Pyramids by MIDES - Maximal Independent Directed Edge Set
Abstract. We present a new method (MIDES) to determine contraction kernels for the construction of graph pyramids. Experimentally the new method has a reduction factor higher than ...
Yll Haxhimusa, Roland Glantz, Walter G. Kropatsch
CVPR
2011
IEEE
14 years 5 months ago
Hyper-graph Matching via Reweighted Random Walks
Establishing correspondences between two feature sets is a fundamental issue in computer vision, pattern recognition, and machine learning. This problem can be well formulated as g...
Jungmin Lee (Seoul National University), Minsu Cho...
AAAI
2004
14 years 11 months ago
Shortest Path Discovery Problems: A Framework, Algorithms and Experimental Results
In this paper we introduce and study Shortest Path Discovery (SPD) problems, a generalization of shortest path problems: In SPD one is given a directed edgeweighted graph and the ...
Csaba Szepesvári