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» Combining Multiple Weak Clusterings
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ICASSP
2010
IEEE
13 years 9 months ago
Clustering disjoint subspaces via sparse representation
Given a set of data points drawn from multiple low-dimensional linear subspaces of a high-dimensional space, we consider the problem of clustering these points according to the su...
Ehsan Elhamifar, René Vidal
PR
2006
127views more  PR 2006»
13 years 9 months ago
Unsupervised possibilistic clustering
In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. Since the FCM memberships do not always explain the degrees of belonging for t...
Miin-Shen Yang, Kuo-Lung Wu
ICML
2000
IEEE
14 years 9 months ago
Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perce...
Daniel Nikovski, Illah R. Nourbakhsh
KDD
2004
ACM
157views Data Mining» more  KDD 2004»
14 years 2 months ago
On detecting space-time clusters
Detection of space-time clusters is an important function in various domains (e.g., epidemiology and public health). The pioneering work on the spatial scan statistic is often use...
Vijay S. Iyengar
CIKM
2008
Springer
13 years 11 months ago
A consensus based approach to constrained clustering of software requirements
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human a...
Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher