登录 注册

估计 (Estimation) and Recovery of a Planted Dense Subgraph from a Single Network Cascade
Estimation and Recovery of a Planted Dense Subgraph from a Single Network Cascade

🔗 访问原文
🔗 Access Paper

📝 摘要
Abstract

We study the inference of a planted dense component in a sparse random graph from a single spreading process. The graph has an Erdős-Rényi background with edge probability $p_n$ and contains a planted dense component of size $n^α$, with $α> 1/2$, whose internal edge density $ξ>0$ is constant. The edge set is unobserved; the data only consist of the successive infection times from a single realization of a continuous-time SI process with independent and exponentially distributed transmission times. We show that the planted dense component leaves a detectable signature in the spreading process: after the exploration enters the dense component, it undergoes a short phase of accelerated growth. By analyzing this phase, we localize its onset and endpoint. These localization results yield consistent estimators of the component-size exponent $α$, the background edge density $p_n$, and the internal edge density $ξ$ from the infection times alone. When the identities of the infected vertices are also observed, we further establish consistent recovery of the planted dense component.

📊 文章统计
Article Statistics

基础数据
Basic Stats

133 浏览
Views
0 下载
Downloads
6 引用
Citations

引用趋势
Citation Trend

阅读国家分布
Country Distribution

阅读机构分布
Institution Distribution

月度浏览趋势
Monthly Views

相关关键词
Related Keywords

影响因子分析
Impact Analysis

5.70 综合评分
Overall Score
引用影响力
Citation Impact
浏览热度
View Popularity
下载频次
Download Frequency

📄 相关文章
Related Articles

海洋智能分析Ocean AI Analysis

正在分析中,请稍候…Analyzing, please wait…
海洋智能体 🌊
海洋智能体
AI科研助手 · 3908篇文献
我看到你正在阅读一篇文献,需要我帮你解读摘要、推荐相关论文,或者分析研究方法论吗?