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Robust Machine Learning Algorithms and Systems: Detection & Mitigation of Adversarial Attacks and Anomalies
Rolling Submissions
NASEM
Description
The Intelligence Community Studies Board of the National Academies of Sciences, Engineering, and Medicine will convene a workshop on December 11-12, 2018 to provide the Intelligence Community (IC) with insights from world-class experts and technologists on methods for assessing the accuracy and veracity of machine-generated analytic intelligence products and techniques for addressing the potential impacts of adversarial manipulation of analytical inputs. To address quality concerns raised during the 2017 ODNI workshop on "Challe...
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Eligible Applicants
- Unrestricted
Funding Type
other
Categories of Funding Activity
- Computers and Information Technology
- Conflict and Security Issues
Grantor Contact Information
Dr. George Coyle, Telephone: (202) 334-3166
Grantor Email
icsb@nas.edu
Other Grantor Informaiton
The National Academies of Sciences, Engineering, and Medicine are private, nonprofit institutions that provide independent, objective advice to inform policy with evidence, spark progress and innovation, and confront challenging issues for the benefit of society. They are comprised of three academies: the National Academy of Sciences, the National Academy of Engineering, and the National Academy of Medicine. The organization convenes hundreds of conferences, workshops, and symposia annually, bringing together leading experts from academia, public, and private sectors. Their work focuses on providing high-quality, evidence-based consensus on complex scientific, engineering, and health-related challenges. They produce peer-reviewed reports, publish scientific journals, and serve as a trusted source of expert advice for policymaking. The National Academies mobilize approximately 6,000 top experts each year who volunteer their time and knowledge to conduct policy studies, workshops, and other activities aimed at addressing critical issues facing the nation and world.
Additional information
The workshop was held in Berkeley, California, to explore methods for ensuring machine-generated analytic products are reliable and how to combat adversarial manipulation. Additional URLs:
https://nap.nationalacademies.org/25534
Supporting Link
https://www.nationalacademies.org/our-work/robust-machine-learning-algorithms-and-systems-detection-mitigation-of-adversarial-attacks-and-anomalies
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