Author
Board on Mathematical Sciences and Analytics
Computer Science and Telecommunications Board
Division on Engineering and Physical Sciences
National Academies of Sciences, Engineering, and Medicine
Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
PublisherNational Academies Press
ReleasedAugust 22, 2019
Copyright2019
ISBN978-0-309-49610-0
Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies

The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11–12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop.

The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11–12, 2018, in Berkeley, California, to discuss robust machine learning algorithms and systems for the detection and mitigation of adversarial attacks and anomalies. This publication summarizes the presentations and discussions from the workshop.

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