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CCGRID
2001
IEEE
15 years 4 months ago
Cluster Computing in the Classroom: Topics, Guidelines, and Experiences
- With the progress of research on cluster computing, more and more universities have begun to offer various courses covering cluster computing. A wide variety of content can be ta...
Amy W. Apon, Rajkumar Buyya, Hai Jin, Jens Mache
117
Voted
CORR
2008
Springer
113views Education» more  CORR 2008»
15 years 23 days ago
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Alain Lelu, Martine Cadot, Pascal Cuxac
100
Voted
ISBI
2007
IEEE
15 years 7 months ago
Multivariate Hypothesis Testing of Dti Data for Tissue Clustering
In this work we investigate the feasibility and effectiveness of unsupervised tissue clustering and classification algorithms for DTI data. Tissue clustering and classification ...
Raisa Z. Freidlin, Yaniv Assaf, Peter J. Basser
93
Voted
KDD
2005
ACM
107views Data Mining» more  KDD 2005»
15 years 6 months ago
Cross-relational clustering with user's guidance
Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information of...
Xiaoxin Yin, Jiawei Han, Philip S. Yu
ECML
2006
Springer
15 years 4 months ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi