Closure properties of uniform convergence of empirical means and PAC learnability under a family of probability measures
Document Type
Article
Publication Date
8-1-2001
Abstract
Open Problem No. 12.2 of (Vidyasagar, A Theory of Learning and Generalization: with Application to Neural Networks and Control Systems, Springer, London, 1997) asks: "Are the properties of uniform convergence of empirical means, and learnability preserved when the family of probability measures is replaced by its closure?" In this note, the question is answered in the affirmative. Further, it is shown that these properties are not preserved in general if the family of probability measures is replaced by its convex closure. An open question is posed as to whether it is possible to replace the family of probability measures by its convex closure in case the family is compact. © 2001 Elsevier Science B.V. All rights reserved.
Identifier
0034910132 (Scopus)
Publication Title
Systems and Control Letters
External Full Text Location
https://doi.org/10.1016/S0167-6911(00)00086-4
ISSN
01676911
First Page
151
Last Page
157
Issue
2
Volume
42
Recommended Citation
    Vidyasagar, M.; Balaji, S.; and Hammer, B., "Closure properties of uniform convergence of empirical means and PAC learnability under a family of probability measures" (2001). Faculty Publications.  15132.
    
    
    
        https://digitalcommons.njit.edu/fac_pubs/15132
    
 
				 
					