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Challenges in machine generation of analytic products from multi-source data : proceedings of a workshop /
"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 chal...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico Congresos, conferencias eBook |
| Idioma: | Inglés |
| Publicado: |
Washington, D.C. :
The National Academies Press,
[2017]
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Casola, Linda Clare, |d 1982- |e rapporteur. |1 https://id.oclc.org/worldcat/entity/E39PCjBt9F7k834DG6tHdKPKbb | |
| 245 | 1 | 0 | |a Challenges in machine generation of analytic products from multi-source data : |b proceedings of a workshop / |c Linda Casola, rapporteur ; Intelligence Community Studies Board, Division on Engineering and Physical Sciences, the National Academies of Sciences, Engineering, Medicine. |
| 264 | 1 | |a Washington, D.C. : |b The National Academies Press, |c [2017] | |
| 264 | 4 | |c ©2017 | |
| 300 | |a 1 online resource (x, 59 pages) : |b color illustrations | ||
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| 505 | 0 | |a Introduction -- Session 1 : plenary -- Session 2 : machine learning from image, video and map data -- Session 3 : Machine learning from natural languages -- Session 4 -- Learning from multi-source data -- Session 5 : learning from noisy, adversarial inputs -- Session 6 : learning from social media -- Session 7 : humans and machines working together with big data -- Session 8 : use of machine learning for privacy ethics -- Session 9 : Evaluation of machine-generated products -- Session 10 : capability technology matrix -- Appendixes. | |
| 520 | |a "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"--Publisher's description. | ||
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Online resource; title from PDF title page (National Academies Press, viewed May 15, 2018). | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Mathematical statistics |x Data processing |v Congresses. | |
| 650 | 0 | |a Machine learning |v Congresses. | |
| 650 | 0 | |a Instructional systems |x Design |v Congresses. | |
| 650 | 6 | |a Statistique mathématique |x Informatique |v Congrès. | |
| 650 | 6 | |a Apprentissage automatique |v Congrès. | |
| 650 | 6 | |a Design pédagogique |v Congrès. | |
| 650 | 7 | |a Instructional systems |x Design |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Mathematical statistics |x Data processing |2 fast | |
| 655 | 7 | |a Conference papers and proceedings |2 fast | |
| 710 | 2 | |a National Academies of Sciences, Engineering, and Medicine (U.S.). |b Intelligence Community Studies Board, |e issuing body. | |
| 711 | 2 | |a Challenges in Machine Generation of Analytic Products from Multi-source Data (Workshop) |d (2017 : |c Washington, D.C.) |j author. | |
| 758 | |i has work: |a Challenges in machine generation of analytic products from multi-source data (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFrHqcpFyDFRKXBjm6mMHd |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a National Academies of Sciences, Engineering, and Medicine. |t Challenges in Machine Generation of Analytic Products from Multi-Source Data : Proceedings of a Workshop. |d Washington, D.C. : National Academies Press, ©2017 |z 9780309465731 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5144008 |z Texto completo |
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