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» Fast algorithms for time series mining
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GRC
2010
IEEE
14 years 11 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
NIPS
1993
14 years 11 months ago
Fast Pruning Using Principal Components
We present a new algorithm for eliminating excess parameters and improving network generalization after supervised training. The method, \Principal Components Pruning (PCP)",...
Asriel U. Levin, Todd K. Leen, John E. Moody
72
Voted
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
15 years 10 months ago
A multinomial clustering model for fast simulation of computer architecture designs
Computer architects utilize simulation tools to evaluate the merits of a new design feature. The time needed to adequately evaluate the tradeoffs associated with adding any new fe...
Kaushal Sanghai, Ting Su, Jennifer G. Dy, David R....
IEAAIE
2009
Springer
15 years 4 months ago
Robust Singular Spectrum Transform
Change Point Discovery is a basic algorithm needed in many time series mining applications including rule discovery, motif discovery, casual analysis, etc. Several techniques for c...
Yasser F. O. Mohammad, Toyoaki Nishida
106
Voted
KDD
2008
ACM
121views Data Mining» more  KDD 2008»
15 years 10 months ago
Reconstructing chemical reaction networks: data mining meets system identification
We present an approach to reconstructing chemical reaction networks from time series measurements of the concentrations of the molecules involved. Our solution strategy combines t...
Yong Ju Cho, Naren Ramakrishnan, Yang Cao