A Brief Survey of Adversarial Concerns in Machine Learning and Deep Learning.
Conference
·
OSTI ID:1573548
Abstract not provided.
- Research Organization:
- Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1573548
- Report Number(s):
- SAND2018-8252PE; 666440
- Country of Publication:
- United States
- Language:
- English
Similar Records
Machine Learning in Adversarial Environments.
Position Paper: Counter-Adversarial Machine Learning is a Critical Concern.
Improving Deep Learning Uncertainty Quantification with Adversarial Training.
Conference
·
Sat Jan 31 23:00:00 EST 2015
·
OSTI ID:1513957
Position Paper: Counter-Adversarial Machine Learning is a Critical Concern.
Conference
·
Mon Jan 31 23:00:00 EST 2022
·
OSTI ID:2001902
Improving Deep Learning Uncertainty Quantification with Adversarial Training.
Conference
·
Wed Jul 01 00:00:00 EDT 2020
·
OSTI ID:1808950