Enki: A Diversity-driven Approach to Test and Train Robust Learning-enabled Systems

IF 2.2 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Michael Austin Langford, B. Cheng
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引用次数: 6

Abstract

ing with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2021 Association for Computing Machinery. 1556-4665/2021/05-ART5 $15.00 https://doi.org/10.1145/3460959 ACM Transactions on Autonomous and Adaptive Systems, Vol. 15, No. 2, Article 5. Publication date: May 2021. 5:2 M. A. Langford and B. H. C. Cheng
Enki:一种多样性驱动的方法来测试和训练健壮的学习支持系统
允许赊账付款。以其他方式复制或重新发布,在服务器上发布或重新分发到列表,需要事先获得特定许可和/或付费。从permissions@acm.org请求权限。©2021计算机械协会。1556-4665/2021/05-ART5 $15.00 https://doi.org/10.1145/3460959 ACM自治与自适应系统学报,第15卷,第2期,第5条。出版日期:2021年5月。[5:2]兰福德m.a.,郑炳昌
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来源期刊
ACM Transactions on Autonomous and Adaptive Systems
ACM Transactions on Autonomous and Adaptive Systems 工程技术-计算机:理论方法
CiteScore
4.80
自引率
7.40%
发文量
9
审稿时长
>12 weeks
期刊介绍: TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community -- and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community - and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. Contributions are expected to be based on sound and innovative theoretical models, algorithms, engineering and programming techniques, infrastructures and systems, or technological and application experiences.
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