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SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
15 years 5 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
CORR
2012
Springer
230views Education» more  CORR 2012»
14 years 3 min ago
Fast Triangle Counting through Wedge Sampling
Graphs and networks are used to model interactions in a variety of contexts, and there is a growing need to be able to quickly assess the qualities of a graph in order to understa...
C. Seshadhri, Ali Pinar, Tamara G. Kolda
ADC
2007
Springer
145views Database» more  ADC 2007»
15 years 10 months ago
The Privacy of k-NN Retrieval for Horizontal Partitioned Data -- New Methods and Applications
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...
Artak Amirbekyan, Vladimir Estivill-Castro
IPMI
2009
Springer
15 years 8 months ago
Dense Registration with Deformation Priors
Abstract. In this paper we propose a novel approach to define task-driven regularization constraints in deformable image registration using learned deformation priors. Our method ...
Ben Glocker, Nikos Komodakis, Nassir Navab, Georgi...
AAAI
2010
15 years 5 months ago
Gaussian Mixture Model with Local Consistency
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
Jialu Liu, Deng Cai, Xiaofei He