清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Network Online Change Point Localization

点(几何) 计算机科学 人工智能 数学 几何学
作者
Yi Yu,Oscar Hernán Madrid Padilla,Daren Wang,Alessandro Rinaldo
出处
期刊:SIAM journal on mathematics of data science [Society for Industrial and Applied Mathematics]
卷期号:6 (1): 176-198
标识
DOI:10.1137/22m1529816
摘要

.We study the following online network change point detection settings: A time series of independent, possibly sparse Bernoulli networks whose distributions might change at an unknown time are observed in a sequential manner, and at each time point, a determination has to be made on whether a change has taken place in the near past. The goal is to detect the change point event (if any has occurred) as quickly as possible, subject to prespecified constraints on the probability or number of false alarms. We propose a CUSUM-based procedure and derive two high-probability upper bounds on its detection delay, i.e., detection delay \(\{ \gtrsim \log(1/\alpha)\frac{1}{\kappa_0^2 n \rho}\); \(\lesssim \log(\Delta/\alpha) \frac{r}{\kappa_0^2 n \rho}\), under a low-rank assumption; \(\lesssim \log(\Delta/\alpha) \frac{\max\{r^2/n, \log(r), 1\}}{\kappa_0^2 n \rho}\), under a block-constancy assumption, where \(\kappa_0, n, \rho, r\), and \(\alpha\) are the normalized jump size, network size, entrywise sparsity, rank sparsity, and overall type I error upper bound. All the model parameters are allowed to vary as \(\Delta\), the unknown change point, diverges. We further establish a minimax lower bound on the detection delay. Under the low-rank assumption and when the rank is of constant order or under the block-constancy assumption when the number of blocks \(r \lesssim \sqrt{n}\), we obtain minimax rates. The above upper bounds are achieved by novel procedures proposed in this paper, designed for quick detection under two different forms of type I error control. The first is based on controlling the overall probability of a false alarm when there are no change points, and the second is based on specifying a lower bound on the expected time of the first false alarm. Extensive experiments show that under different scenarios and the aforementioned forms of type I error control, our proposed approaches well outperform state-of-the-art methods.Keywordsdynamic networksonline change point detectionminimax optimalityMSC codes62C2062L99
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI2S应助精明晓刚采纳,获得10
4秒前
10秒前
瓣落的碎梦完成签到,获得积分10
11秒前
Destiny发布了新的文献求助10
14秒前
矢思然完成签到,获得积分10
15秒前
安琪琪完成签到 ,获得积分10
19秒前
50秒前
轩辕中蓝完成签到 ,获得积分10
54秒前
张凡完成签到 ,获得积分10
54秒前
深情安青应助科研通管家采纳,获得10
58秒前
婉莹完成签到 ,获得积分0
1分钟前
朵朵完成签到,获得积分10
1分钟前
ggg完成签到 ,获得积分10
1分钟前
myth完成签到,获得积分10
1分钟前
LuciusHe完成签到,获得积分10
1分钟前
Tong完成签到,获得积分0
1分钟前
乐观的星月完成签到 ,获得积分10
2分钟前
落落完成签到 ,获得积分0
2分钟前
momoni完成签到 ,获得积分10
2分钟前
2分钟前
rpe发布了新的文献求助10
2分钟前
Lyanph完成签到 ,获得积分10
2分钟前
2分钟前
领导范儿应助科研通管家采纳,获得10
2分钟前
CC发布了新的文献求助10
2分钟前
Dreamhappy完成签到,获得积分10
3分钟前
chichenglin完成签到 ,获得积分0
3分钟前
3分钟前
gszy1975发布了新的文献求助10
3分钟前
凤里完成签到 ,获得积分10
3分钟前
fogsea完成签到,获得积分0
4分钟前
yao完成签到 ,获得积分10
4分钟前
韩寒完成签到 ,获得积分10
4分钟前
王佳豪完成签到,获得积分10
4分钟前
路路完成签到 ,获得积分10
4分钟前
4分钟前
曹国庆完成签到 ,获得积分10
5分钟前
StonesKing完成签到,获得积分20
5分钟前
tmobiusx完成签到,获得积分10
5分钟前
xun完成签到,获得积分10
5分钟前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3990629
求助须知:如何正确求助?哪些是违规求助? 3532220
关于积分的说明 11256552
捐赠科研通 3271057
什么是DOI,文献DOI怎么找? 1805229
邀请新用户注册赠送积分活动 882302
科研通“疑难数据库(出版商)”最低求助积分说明 809234