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.
- FrontMatter
- Acknowledgments
- Contents
- 1 Introduction
- 2 Plenary Session
- 3 Adversarial Attacks
- 4 Detection and Mitigation of Adversarial Attacks and Anomalies
- 5 Enablers of Machine Learning Algorithms and Systems
- 6 Recent Trends in Machine Learning, Parts 1 and 2
- 7 Plenary Session
- 8 Recent Trends in Machine Learning, Part 3
- 9 Machine Learning Systems
- References
- Appendixes
- Appendix A: Biographical Sketches of Workshop Planning Committee
- Appendix B: Workshop Agenda
- Appendix C: Workshop Statement of Task
- Appendix D: Capability Technology Matrix
- Appendix E: Acronyms
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