网络分布建模的统计方法Statistical Methods for Modeling Network Distributions |
|
课程网址: | https://videolectures.net/videos/kdd2016_neville_network_distribu... |
主讲教师: | Jennifer Neville |
开课单位: | KDD 2016研讨会 |
开课时间: | 2016-10-12 |
课程语种: | 英语 |
中文简介: | 最近对分析复杂系统网络结构的兴趣推动了对网络结构模型和算法的大量研究,以自动发现用于预测模型的模式。然而,稳健的统计模型可以准确地表示图总体上的分布,并从这些分布中有效地采样,对于评估分析算法的性能和发现模式的重要性至关重要。然而,与度量空间不同,图的空间呈现出一种组合结构,这对准确估计和有效采样/推理提出了重大的理论和实践挑战。在本次演讲中,我将讨论我们最近在网络分布建模方面的工作,包括有属性和无属性,并概述这些方法如何用于推理和评估。 |
课程简介: | The recent interest in analyzing the network structure of complex systems has fueled a large body of research on both models of network structure and algorithms to automatically discover patterns for use in predictive models. However, robust statistical models, which can accurately represent distributions over graph populations, and sample efficiently from those distributions, are critical to assess the evaluate the performance of analytic algorithms and the significance of discovered patterns. However, unlike metric spaces, the space of graphs exhibits a combinatorial structure that poses significant theoretical and practical challenges to accurate estimation and efficient sampling/inference. In this talk, I will discuss our recent work on modeling distributions of networks, both attributed and unattributed, and outline how the methods can be used for inference and evaluation. |
关 键 词: | 网络分布建模; 统计方法; 网络结构 |
课程来源: | 视频讲座网 |
数据采集: | 2025-01-07:liyq |
最后编审: | 2025-01-07:liyq |
阅读次数: | 15 |