Paper Info
Title
Input Reconstruction Reliability Estimation
Abstract
The ability to identify and reason about novel aspects of their input would greatly enhance the capabilities of artificial neural networks. The extent of the novelty could be used to judge the appropriateness of individual networks for the task to be performed. The location and shape of novel features could be employed to identify the unusual components of the input and to choose an appropriate response.
Year
DOI
Venue
1992
10.1007/978-1-4615-3192-0_9
NIPS
Keywords
Field
DocType
input reconstruction reliability estimation,artificial neural network
ENCODE,Computer science,Reconstruction error,Artificial intelligence,Perceptron,Machine learning
Conference
ISBN
Citations 
PageRank 
1-55860-274-7
8
16.19
References 
Authors
4
1
Name
Order
Citations
PageRank
Dean Pomerleau11039283.23