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KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 6 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han
ICPP
2000
IEEE
15 years 10 months ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary
DATAMINE
2006
89views more  DATAMINE 2006»
15 years 6 months ago
Scalable Clustering Algorithms with Balancing Constraints
Clustering methods for data-mining problems must be extremely scalable. In addition, several data mining applications demand that the clusters obtained be balanced, i.e., be of ap...
Arindam Banerjee, Joydeep Ghosh
IJHPCA
2008
131views more  IJHPCA 2008»
15 years 6 months ago
De Novo Ultrascale Atomistic Simulations On High-End Parallel Supercomputers
We present a de novo hierarchical simulation framework for first-principles based predictive simulations of materials and their validation on high-end parallel supercomputers and ...
Aiichiro Nakano, Rajiv K. Kalia, Ken-ichi Nomura, ...
ICDE
2005
IEEE
157views Database» more  ICDE 2005»
16 years 7 months ago
MoDB: Database System for Synthesizing Human Motion
Enacting and capturing real motion for all potential scenarios is terribly expensive; hence, there is a great demand to synthetically generate realistic human motion. However, it ...
Timothy Edmunds, S. Muthukrishnan, Subarna Sadhukh...