Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities
Date
2019Author
Zhang, Jeff JunLiu, Kang
Khalid, Faiq
Hanif, Muhammad Abdullah
Rehman, Semeen
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Artussi, Alessandro
Shafique, Muhammad
Garg, Siddharth
ISBN
978-1-4503-6725-7Publisher
ACMPlace of publication
Las Vegas NV USASource
Proceedings of the 56th Annual Design Automation Conference 2019Pages
1-4Google Scholar check
Metadata
Show full item recordAbstract
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.