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IPPS
2006
IEEE
14 years 1 months ago
Empowering a helper cluster through data-width aware instruction selection policies
Narrow values that can be represented by less number of bits than the full machine width occur very frequently in programs. On the other hand, clustering mechanisms enable cost- a...
Osman S. Unsal, Oguz Ergin, Xavier Vera, Antonio G...
ISNN
2011
Springer
12 years 10 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
ICASSP
2007
IEEE
14 years 1 months ago
Feature Selection Based on Fisher Ratio and Mutual Information Analyses for Robust Brain Computer Interface
This paper proposes a novel feature selection method based on twostage analysis of Fisher Ratio and Mutual Information for robust Brain Computer Interface. This method decomposes ...
Tran Huy Dat, Cuntai Guan
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 8 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
ICML
1994
IEEE
13 years 11 months ago
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
With the goal of reducing computational costs without sacrificing accuracy, we describe two algorithms to find sets of prototypes for nearest neighbor classification. Here, the te...
David B. Skalak