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» A clustering method that uses lossy aggregation of data
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ICPR
2008
IEEE
14 years 3 months ago
Clustering by evidence accumulation on affinity propagation
If there are more clusters than the ideal, each intrinsic cluster will be split into several subsets. Theoretically, this split can be arbitrary and neighboring data points have a ...
Xuqing Zhang, Fei Wu, Yueting Zhuang
CORR
2002
Springer
113views Education» more  CORR 2002»
13 years 9 months ago
Robust Global Localization Using Clustered Particle Filtering
Global mobile robot localization is the problem of determining a robot's pose in an environment, using sensor data, when the starting position is unknown. A family of probabi...
Javier Nicolás Sánchez, Adam Milstei...
ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
13 years 7 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König
CVPR
2012
IEEE
11 years 11 months ago
Evaluation of super-voxel methods for early video processing
Supervoxel segmentation has strong potential to be incorporated into early video analysis as superpixel segmentation has in image analysis. However, there are many plausible super...
Chenliang Xu, Jason J. Corso
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
14 years 9 months ago
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets
We present a novel algorithm called Clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, Clicks mines subs...
Mohammed Javeed Zaki, Markus Peters, Ira Assent, T...