Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities

J. Zhang, Kang Liu, Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, T. Theocharides, Alessandro Artussi, M. Shafique, S. Garg
{"title":"Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities","authors":"J. Zhang, Kang Liu, Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, T. Theocharides, Alessandro Artussi, M. Shafique, S. Garg","doi":"10.1145/3316781.3323472","DOIUrl":null,"url":null,"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.","PeriodicalId":391209,"journal":{"name":"Proceedings of the 56th Annual Design Automation Conference 2019","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 56th Annual Design Automation Conference 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3316781.3323472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 28

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
构建强大的机器学习系统:当前进展,研究挑战和机遇
机器学习,特别是深度学习,几乎被用于生活的各个方面,以方便人类,特别是在移动和基于物联网(IoT)的应用中。由于其最先进的性能,深度学习也被用于安全关键应用,例如自动驾驶汽车。可靠性和安全性是这些应用程序所需的两个关键特性,因为它们可能对人类的生活产生影响。为此,在本文中,我们重点介绍了基于机器学习应用的鲁棒系统领域的当前进展、挑战和研究机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
LODESTAR DHOOM Filianore ChipSecure MRLoc
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1