Challenges in machine generation of analytic products from multi-source data : proceedings of a workshop.

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The Intelligence Community Studies Board of the National Academies of Sciences, Engineering, and Medicine convened a workshop on August 9-10, 2017 to examine challenges in machine generation of analytic products from multi-source data. Workshop speakers and participants discussed research challenges...

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Bibliographic Details
Corporate Author: National Academies of Sciences, Engineering, and Medicine (U.S.)
Other Authors: Casola, Linda Clare, 1982- (rapporteur.)
Language:English
Published: Washington, D.C. : National Academies Press, 2017.
Subjects:
Mathematical statistics > Data processing.
Statistics.
Social sciences > Statistical methods.
Physical Description:x, 59 pages : illustrations (some color), color maps ; 28 cm
Also issued online.
Format: Book
Description
Summary:
The Intelligence Community Studies Board of the National Academies of Sciences, Engineering, and Medicine convened a workshop on August 9-10, 2017 to examine challenges in machine generation of analytic products from multi-source data. Workshop speakers and participants discussed research challenges related to machine-based methods for generating analytic products and for automating the evaluation of these products, with special attention to learning from small data, using multi-source data, adversarial learning, and understanding the human-machine relationship. This publication summarizes the presentations and discussions from the workshop.
Call Number:QA276.4 .C43 2017
ISBN:0309465737
9780309465731
Additional Physical Form:
Also issued online.
Action Note:
copy1 Committed to retain 20200101 20341231 MI-SPI http://www.mcls.org/engagement/mi-spi/ MiEM