| dc.date.accessioned | 2020-10-14T19:38:27Z | |
| dc.date.available | 2020-10-14T19:38:27Z | |
| dc.date.issued | 2020-06-26 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/127997 | |
| dc.description.abstract | “Our ultimate goal is to provide the researchers and stakeholders of our community with a set of robustness tools, techniques, and best practices so that they can embrace the great promise of machine learning technology with the confidence that they can meet the safety and security demands that are specific to the national security
domain,” | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | MIT Lincoln Laboratory | en_US |
| dc.relation.ispartofseries | The Bulletin; | |
| dc.rights | Attribution-NoDerivs 3.0 United States | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
| dc.subject | Supercomputing | en_US |
| dc.subject | Cyber Security | en_US |
| dc.subject | Artificial Intelligence | en_US |
| dc.subject | Information Sciences | en_US |
| dc.subject | LLSC | en_US |
| dc.subject | Machine Learning | en_US |
| dc.title | Staff Build Robust Algorithms to Strengthen Machine Learning Methods | en_US |
| dc.type | Article | en_US |
