Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies
- National Academies of Sciences, Engineering, and Medicine
- Division on Engineering and Physical Sciences
- Computer Science and Telecommunications Board
- Board on Mathematical Sciences and Analytics
- Intelligence Community Studies Board
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Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies is written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. It's available with International Standard Book Number or ISBN identification 0309496128 (ISBN 10) and 9780309496124 (ISBN 13).
The Intelligence Community Studies Board (ICSB) of the National Academies of Sciences, Engineering, and Medicine convened a workshop on December 11â€"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.
