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Challenges In Machine Generation Of Analytic Products From Multisource Data Proceedings Of A Workshop 1st Edition And Medicine Engineering National Academies Of Sciences Division On Engineering And Physical Sciences Intelligence Community Studies Board Linda Casola

  • SKU: BELL-51747340
Challenges In Machine Generation Of Analytic Products From Multisource Data Proceedings Of A Workshop 1st Edition And Medicine Engineering National Academies Of Sciences Division On Engineering And Physical Sciences Intelligence Community Studies Board Linda Casola
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Challenges In Machine Generation Of Analytic Products From Multisource Data Proceedings Of A Workshop 1st Edition And Medicine Engineering National Academies Of Sciences Division On Engineering And Physical Sciences Intelligence Community Studies Board Linda Casola instant download after payment.

Publisher: National Academies Press
File Extension: EPUB
File size: 1.91 MB
Pages: 71
Author: and Medicine Engineering National Academies of Sciences; Division on Engineering and Physical Sciences; Intelligence Community Studies Board; Linda Casola
ISBN: 9780309465748, 0309465745
Language: English
Year: 2017
Edition: 1

Product desciption

Challenges In Machine Generation Of Analytic Products From Multisource Data Proceedings Of A Workshop 1st Edition And Medicine Engineering National Academies Of Sciences Division On Engineering And Physical Sciences Intelligence Community Studies Board Linda Casola by And Medicine Engineering National Academies Of Sciences; Division On Engineering And Physical Sciences; Intelligence Community Studies Board; Linda Casola 9780309465748, 0309465745 instant download after payment.

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.

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