A Note on Maximizing Regularized Submodular Functions Under Streaming

被引：0
|
作者：
Gong, Qinqin [1 ]
Meng, Kaiqiao [1 ]
Yang, Ruiqi [1 ]
Zhang, Zhenning [1 ]
机构：
[1] Beijing Univ Technol, Beijing Inst Sci & Engn Comp, Beijing 100124, Peoples R China
来源：
TSINGHUA SCIENCE AND TECHNOLOGY | 2023年 / 28卷 / 06期
基金：
北京市自然科学基金; 中国国家自然科学基金; 中国博士后科学基金;
关键词：
submodular optimization; regular model; streaming algorithms; threshold technique; FUNCTION SUBJECT; MAXIMIZATION;
D O I：
10.26599/TST.2022.9010068
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Recent progress in maximizing submodular functions with a cardinality constraint through centralized and streaming modes has demonstrated a wide range of applications and also developed comprehensive theoretical guarantees. The submodularity was investigated to capture the diversity and representativeness of the utilities, and the monotonicity has the advantage of improving the coverage. Regularized submodular optimization models were developed in the latest studies (such as a house on fire), which aimed to sieve subsets with constraints to optimize regularized utilities. This study is motivated by the setting in which the input stream is partitioned into several disjoint parts, and each part has a limited size constraint. A first threshold-based bicriteria (1/3, 2/3)-approximation for the problem is provided.
引用
收藏
页码：1023 / 1029
页数：7
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