DocumentCode :
3318581
Title :
Some notes on the stability of learning
Author :
Yufeng Deng ; Guo, Jun ; Luo, Shoushan
Author_Institution :
Sch. of Inf. Eng., Beijing Univ. of Posts & Telecommun., China
fYear :
2005
fDate :
30 Oct.-1 Nov. 2005
Firstpage :
756
Lastpage :
759
Abstract :
Learning theory based on ERM principle, especially promoted by VC theory provides some conditions on the hypothesis space to ensure generalization. However, several successful learning algorithms including regularization learning, SVM, bagging and boost are not strictly ERM. So, scientists are looking for new foundation of learning. Stability conditions are perhaps new foundation. We give an exponential bound for generalization performance based on concentration inequality with strong CV stability.
Keywords :
generalisation (artificial intelligence); learning (artificial intelligence); CV stability; VC theory; empirical risk minimization principle; learning theory; Bagging; Learning systems; Machine learning; Mathematics; Risk management; Stability; Support vector machines; Topology; Virtual colonoscopy; Zinc; Concentration inequality; generalization bound; strong CV stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Language Processing and Knowledge Engineering, 2005. IEEE NLP-KE '05. Proceedings of 2005 IEEE International Conference on
Print_ISBN :
0-7803-9361-9
Type :
conf
DOI :
10.1109/NLPKE.2005.1598837
Filename :
1598837
Link To Document :
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