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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
16 years 11 days ago
Heterogeneous source consensus learning via decision propagation and negotiation
Nowadays, enormous amounts of data are continuously generated not only in massive scale, but also from different, sometimes conflicting, views. Therefore, it is important to conso...
Jing Gao, Wei Fan, Yizhou Sun, Jiawei Han
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 7 days ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
KDD
2001
ACM
166views Data Mining» more  KDD 2001»
16 years 7 days ago
Generalized clustering, supervised learning, and data assignment
Clustering algorithms have become increasingly important in handling and analyzing data. Considerable work has been done in devising effective but increasingly specific clustering...
Annaka Kalton, Pat Langley, Kiri Wagstaff, Jungsoo...
ICPR
2008
IEEE
15 years 6 months ago
A clustering algorithm combine the FCM algorithm with supervised learning normal mixture model
In this paper we propose a new clustering algorithm which combines the FCM clustering algorithm with the supervised learning normal mixture model; we call the algorithm as the FCM...
Wei Wang, Chunheng Wang, Xia Cui, Ai Wang
ICPR
2008
IEEE
15 years 6 months ago
A uniformity criterion and algorithm for data clustering
We propose a novel multivariate uniformity criterion for testing uniformity of point density in an arbitrary dimensional point pattern . An unsupervised, nonparametric data cluste...
Sanketh Shetty, Narendra Ahuja