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利用高阶结构进行网络社区检测AI 解读

Summary In many real-world networks, it is often observed that subgraphs or higher-order structures of certain configurations, e.g., triangles and by-fans, are overly abundant compared to standard randomly generated networks (Milo et al., 2002). However, statistical models accounting for this phenomenon are limited, especially when community structure is of interest. This limitation is coupled with a lack of community detection methods that leverage subgraphs or higher-order…

具有共享结构的多层网络潜在空间模型AI 解读

Summary Latent space models are frequently used for modelling single-layer networks and include many popular special cases, such as the stochastic block model and the random dot product graph. However, they are not well developed for more complex network structures, which are becoming increasingly common in practice. In this article we propose a new latent space model for multiplex networks, i.e., multiple heterogeneous networks observed on a shared node set. Multiplex…

《多元回归中降秩估计量的自由度》证明缺陷说明AI 解读

Biometrika (2015), 102, pp. 457–77 The argument given in the paper that Stein’s formula can be applied to the reduced-rank regression estimator is unfortunately incomplete. A full proof may be found in Hansen (2017). We thank Niels Richard Hansen for pointing out a deficiency in the proof in the paper.