DocumentCode
2962384
Title
Explicit update vs implicit update
Author
He, Wenwu ; Jiang, Hui
fYear
2008
fDate
1-8 June 2008
Firstpage
3441
Lastpage
3447
Abstract
In this paper, the problem of implicit online learning is considered. A tighter convergence bound is derived, which demonstrates theoretically the feasibility of implicit update for online learning. Then we combine SMD with implicit update technique and the resulting algorithm possesses the inherent stability. Theoretical result is well corroborated by the experiments we performed which also indicate that combining SMD with implicit update technique is another promising way for online learning.
Keywords
computer aided instruction; metacomputing; stochastic processes; SMD; implicit online learning; implicit update technique; Computers; Convergence; Helium; Hilbert space; Kernel; Loss measurement; Optimization methods; Processor scheduling; Stability; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634288
Filename
4634288
Link To Document