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INVITED: Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities.
- Source :
- DAC: Annual ACM/IEEE Design Automation Conference; 2019, Issue 56, p1231-1234, 4p
- Publication Year :
- 2019
-
Abstract
- Machine learning, in particular deep learning, is being used in almost all the aspects of life to facilitate humans, specifically in mobile and Internet of Things (IoT)-based applications. Due to its state-of-the-art performance, deep learning is also being employed in safety-critical applications, for instance, autonomous vehicles. Reliability and security are two of the key required characteristics for these applications because of the impact they can have on human's life. Towards this, in this paper, we highlight the current progress, challenges and research opportunities in the domain of robust systems for machine learning-based applications. [ABSTRACT FROM AUTHOR]
- Subjects :
- MACHINE learning
DEEP learning
INTERNET of things
AUTONOMOUS vehicles
ROBUST control
Subjects
Details
- Language :
- English
- ISSN :
- 0738100X
- Issue :
- 56
- Database :
- Complementary Index
- Journal :
- DAC: Annual ACM/IEEE Design Automation Conference
- Publication Type :
- Conference
- Accession number :
- 155539612
- Full Text :
- https://doi.org/10.1145/3316781.3323472