Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop (2019)
Chapter: Appendix B: Workshop Agenda
Visit
NAP.edu/10766
to get more information about this book, to buy it in print, or to
download it as a free PDF.
Previous Chapter:
Appendix A: Biographical Sketches of Workshop Planning Committee
B
Next Chapter: Appendix C: Workshop Statement of Task
Suggested Citation:
"Appendix B: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2019. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. Washington, DC: The National Academies Press.
doi: 10.17226/25534.
B
Workshop Agenda
DAY 1: DECEMBER 11, 2018
Session 1: Plenary
| 8:00 AM | Sponsor Remarks and Expectations of the Workshop |
| David M. Isaacson, Office of the Director of National Intelligence | |
| 8:15 | Generation of Capability Technology Matrix Tables |
| Rama Chellappa, Planning Committee Chair, University of Maryland, College Park | |
| George Coyle, Study Director, Intelligence Community Studies Board, National Academies of Sciences, Engineering, and Medicine | |
| 8:30 | Recent Advances in Machine Learning |
| Michael Jordan, University of California, Berkeley | |
| 9:30 | Machine Learning on Perception: Hype vs. Hope |
| Ruzena Bajcsy, University of California, Berkeley | |
| 10:30 | Break |
Session 2: Adversarial Attacks
| 11:00 | Media Forensics |
| Matthew Turek, Defense Advanced Research Projects Agency | |
| 11:45 | Forensic Techniques |
| Hany Farid, Dartmouth College |
Suggested Citation:
"Appendix B: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2019. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. Washington, DC: The National Academies Press.
doi: 10.17226/25534.
| 12:30 PM | Lunch |
Session 3: Detection and Mitigation of Adversarial Attacks and Anomalies
| 1:30 | Joysula Rao, IBM Corporation |
| 2:15 | Circumventing Defenses to Adversarial Examples |
| Anish Athalye, Massachusetts Institute of Technology | |
| 3:00 | Break |
Session 4: Enablers of Machine Learning Algorithms and Systems
| 3:30 | Impact of Neuroscience on Data Science for Perception |
| John Tsotsos, York University, Canada | |
| 5:30 | Capability Technology Matrix Tables Preparation |
| 6:00 | Adjourn for the Day |
DAY 2: DECEMBER 12, 2018
| 8:00 AM | Sponsor Remarks |
| David M. Isaacson, Office of the Director of National Intelligence |
Session 5: Recent Trends in Machine Learning—1
| 8:15 | On Open Set and Adversarial Issues in Machine Learning |
| Terry Boult, University of Colorado, Colorado Springs | |
| 9:00 | GANs for Domain Adaptation and Security Against Attacks |
| Rama Chellappa, University of Maryland, College Park | |
| 9:45 | Break |
Session 6: Recent Trends in Machine Learning—2
| 10:00 | Recent Advances in Optimization for Machine Learning |
| Tom Goldstein, University of Maryland | |
| 10:45 | Forecasting Using Machine Learning |
| Aram Galstyan, Information Sciences Institute, University of Southern California |
Suggested Citation:
"Appendix B: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2019. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. Washington, DC: The National Academies Press.
doi: 10.17226/25534.
Session 7: Plenary Session
| 11:30 | Plenary Talk |
| Dawn Song, University of California, Berkeley | |
| 12:30 PM | Lunch |
Session 8: Recent Trends in Machine Learning—3
| 1:30 | Domain Adaptation |
| Judy Hoffman, Georgia Institute of Technology | |
| 2:15 | Explainable Machine Learning |
| Anna Rohrbach, University of California, Berkeley | |
| 3:00 | Break |
Session 9: Machine Learning System
| 3:15 | Building Domain-Specific Knowledge with Human-in-the-Loop |
| Yunyao Li, IBM Corporation | |
| 4:00 | Robust Design of Machine Learning Systems |
| Anthony Hoogs, Kitware, Inc. |
Session 10: Capability Technology Matrix Tables
| 4:45 | Discussion on Preparing the Capability Technology Matrix Tables |
| 5:30 | Adjourn Workshop |
Suggested Citation:
"Appendix B: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2019. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. Washington, DC: The National Academies Press.
doi: 10.17226/25534.
Suggested Citation:
"Appendix B: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2019. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. Washington, DC: The National Academies Press.
doi: 10.17226/25534.
Suggested Citation:
"Appendix B: Workshop Agenda." National Academies of Sciences, Engineering, and Medicine. 2019. Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop. Washington, DC: The National Academies Press.
doi: 10.17226/25534.
Subscribe to Emails from the National Academies
Stay up to date on activities, publications, and events by subscribing to email updates.