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ICML
2004
IEEE
16 years 7 months ago
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Chris H. Q. Ding, Xiaofeng He
KDD
2006
ACM
228views Data Mining» more  KDD 2006»
16 years 7 months ago
Algorithms for time series knowledge mining
Temporal patterns composed of symbolic intervals are commonly formulated with Allen's interval relations originating in temporal reasoning. This representation has severe dis...
Fabian Mörchen
KDD
2004
ACM
302views Data Mining» more  KDD 2004»
16 years 7 months ago
Redundancy based feature selection for microarray data
In gene expression microarray data analysis, selecting a small number of discriminative genes from thousands of genes is an important problem for accurate classification of diseas...
Lei Yu, Huan Liu
ICCD
2005
IEEE
108views Hardware» more  ICCD 2005»
16 years 3 months ago
Methods for Modeling Resource Contention on Simultaneous Multithreading Processors
Simultaneous multithreading (SMT) seeks to improve the computation throughput of a processor core by sharing primary resources such as functional units, issue bandwidth, and cache...
Tipp Moseley, Dirk Grunwald, Joshua L. Kihm, Danie...
ACHI
2009
IEEE
16 years 1 months ago
Nervixxx: A Video Performance System with Neural Interfaces
Nervixxx introduces neural computing to overcome the limit of conventional performance systems1 that uses tangible computing and physical computing. Specifically, we utilized the ...
Satoru Tokuhisa