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ICASSP
2010
IEEE
13 years 4 months ago
A supervisory approach to semi-supervised clustering
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...
Bryan Conroy, Yongxin Taylor Xi, Peter J. Ramadge
CLUSTER
2005
IEEE
14 years 1 months ago
Fast Query Processing by Distributing an Index over CPU Caches
Data intensive applications on clusters often require requests quickly be sent to the node managing the desired data. In many applications, one must look through a sorted tree str...
Xiaoqin Ma, Gene Cooperman
NIPS
2004
13 years 8 months ago
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, ...
DASFAA
2009
IEEE
115views Database» more  DASFAA 2009»
14 years 2 months ago
TRUSTER: TRajectory Data Processing on ClUSTERs
With the continued advancements in location-based services involved infrastructures, large amount of time-based location data are quickly accumulated. Distributed processing techni...
Bin Yang 0002, Qiang Ma, Weining Qian, Aoying Zhou
DIS
2006
Springer
13 years 11 months ago
A Novel Framework for Discovering Robust Cluster Results
We propose a novel method, called heterogeneous clustering ensemble (HCE), to generate robust clustering results that combine multiple partitions (clusters) derived from various cl...
Hye-Sung Yoon, Sang-Ho Lee, Sung-Bum Cho, Ju Han K...