A framework for fitting sparse data
Published in arXiv (Cornell University) • Jul 4, 2014
NobleIDNI7P58W27R96S55
Authors:,,
Reza Hosseini
Akimichi Takemura
Kiros Berhane
Abstract
This paper develops a framework for fitting functions with domains in the Euclidean space, when data are sparse but a slow variation allows for a useful fit. We measure the variation by Lipschitz Bound (LB). Functions which admit smaller LB are considered to vary more slowly. Since most functions in...
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