# Learning Modular Structures from Network Data and Node Variables

@inproceedings{Azizi2014LearningMS, title={Learning Modular Structures from Network Data and Node Variables}, author={Elham Azizi and Edoardo M. Airoldi and James E. Galagan}, booktitle={International Conference on Machine Learning}, year={2014} }

A standard technique for understanding underlying dependency structures among a set of variables posits a shared conditional probability distribution for the variables measured on individuals within a group. This approach is often referred to as module networks, where individuals are represented by nodes in a network, groups are termed modules, and the focus is on estimating the network structure among modules. However, estimation solely from node-specific variables can lead to spurious…

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