DocumentCode
2388239
Title
A Symmetrical Linear Transform Learning Algorithm on Quantum Group
Author
He, Shuping ; Li, Fanzhang
Author_Institution
Soochow Univ., Suzhou
fYear
2007
fDate
2-4 Nov. 2007
Firstpage
724
Lastpage
724
Abstract
Based on Lie group machine learning theory and noncommutative features of quantum group, this paper proposes a symmetrical linear transform learning algorithm on quantum group and have it applied on DNA sequence classification. The comparing between quantum group classifier and the widely used SVM is also presented.
Keywords
DNA; Lie groups; biology computing; learning (artificial intelligence); pattern classification; quantum theory; sequences; support vector machines; transforms; DNA sequence classification; Lie group theory; SVM; machine learning; quantum group; symmetrical linear transform learning algorithm; Algebra; Computer science; DNA; Geometry; Helium; Machine learning; Machine learning algorithms; Quantum computing; Quantum mechanics; Sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3032-1
Type
conf
DOI
10.1109/GrC.2007.37
Filename
4403195
Link To Document