Search Results for author:
Found 9 papers, 4 papers with code
Detectability of hierarchical communities in networks
We study the problem of recovering a planted hierarchy of partitions in a network.
Hierarchical community structure in networks
A great deal of effort has gone into trying to detect and study these structures.
Network constraints on the mixing patterns of binary node metadata
We consider the network constraints on the bounds of the assortativity coefficient, which measures the tendency of nodes with the same attribute values to be interconnected.
Social and Information Networks Data Analysis, Statistics and Probability Physics and Society
Community detection in networks without observing edges
We develop a Bayesian hierarchical model to identify communities in networks for which we do not observe the edges directly, but instead observe a series of interdependent signals for each of the nodes.
Graph-based semi-supervised learning for relational networks
Typically this problem is confounded with the problem of graph-based semi-supervised learning (GSSL), because both problems represent the data as a graph and predict the missing class labels of nodes.
The ground truth about metadata and community detection in networks
We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models.
Detectability thresholds and optimal algorithms for community structure in dynamic networks
We study the fundamental limits on learning latent community structure in dynamic networks.
Detecting change points in the large-scale structure of evolving networks
Interactions among people or objects are often dynamic in nature and can be represented as a sequence of networks, each providing a snapshot of the interactions over a brief period of time.
Active Discovery of Network Roles for Predicting the Classes of Network Nodes
In other cases, however, this is not true, and the way that nodes link in a network exhibits a different, more complex relationship to their attributes.
