南方科技大学知识苑(SUSTech KC): Sequence selection by Pareto optimization

题名	Sequence selection by Pareto optimization
作者	Qian，Chao 1; Feng，Chao 1; Tang，Ke2
发表日期	2018
ISSN	1045-0823
会议录名称	IJCAI International Joint Conference on Artificial Intelligence
卷号	2018-July
页码	1485-1491
会议地点	Stockholm, Sweden
出版者	International Joint Conferences on Artificial Intelligence
摘要	The problem of selecting a sequence of items from a universe that maximizes some given objective function arises in many real-world applications. In this paper, we propose an anytime randomized iterative approach POSEQSEL, which maximizes the given objective function and minimizes the sequence length simultaneously. We prove that for any previously studied objective function, POSEQSEL using a reasonable time can always reach or improve the best known approximation guarantee. Empirical results exhibit the superior performance of POSEQSEL.
学校署名	其他
语种	英语
相关链接	[Scopus记录]
收录类别	EI
资助项目	Shenzhen Science and Technology Innovation Commission[ZDSYS201703031748284] ; National Natural Science Foundation of China[61672478] ; [2016QNRC001]
EI入藏号	20184406016148
EI主题词	Artificial intelligence ; Multiobjective optimization
EI分类号	Artificial Intelligence:723.4 ; Optimization Techniques:921.5
Scopus记录号	2-s2.0-85055706595
来源库	Scopus
成果类型	会议论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/44352
专题	工学院_计算机科学与工程系
作者单位	1.Anhui Province Key Lab of Big Data Analysis and Application, University of Science and Technology of China, ,Hefei,230027,China 2.Shenzhen Key Lab of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, ,Shenzhen,518055,China
推荐引用方式 GB/T 7714	Qian，Chao,Feng，Chao,Tang，Ke. Sequence selection by Pareto optimization[C]:International Joint Conferences on Artificial Intelligence,2018:1485-1491.