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Learning a Probability Distribution Efficiently and ReliablyA new algorithm, called the CDF-Inversion Algorithm, is described. Using it, one can efficiently learn a probability distribution over a finite set to a specified accuracy and confidence. The algorithm can be extended to learn joint distributions over a vector space. Some implementation results are described.
Document ID
19990116077
Acquisition Source
Ames Research Center
Document Type
Other
Authors
Laird, Philip
(NASA Ames Research Center Moffett Field, CA United States)
Gamble, Evan
(NASA Ames Research Center Moffett Field, CA United States)
Date Acquired
August 19, 2013
Publication Date
October 1, 1988
Subject Category
Statistics And Probability
Report/Patent Number
RIA-88-10-10-0
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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