939 citations · 3.6k across the 51 of their papers we have counts for
11 papers · 1 filter
Interpretable Network-assisted Random Forest+
Tiffany M. Tang, Elizaveta Levina, Ji Zhu
Machine learning algorithms often assume that training samples are independent. When data points are connected by a network, the induced dependency between samples is both a challe…
Fair Information Spread on Social Networks with Community Structure
Octavio Mesner, Elizaveta Levina, Ji Zhu
Information spread through social networks is ubiquitous. Influence maximiza- tion (IM) algorithms aim to identify individuals who will generate the greatest spread through the soc…
High-dimensional Gaussian graphical model for network-linked data
Tianxi Li, Cheng Qian, Elizaveta Levina +1
Graphical models are commonly used to represent conditional dependence relationships between variables. There are multiple methods available for exploring them from high-dimensiona…
Community Detection in Networks with Node Features
Yuan Zhang, Elizaveta Levina, Ji Zhu
Many methods have been proposed for community detection in networks, but most of them do not take into account additional information on the nodes that is often available in practi…
Estimating network edge probabilities by neighborhood smoothing
Yuan Zhang, Elizaveta Levina, Ji Zhu
The estimation of probabilities of network edges from the observed adjacency matrix has important applications to predicting missing links and network denoising. It has usually bee…
Estimating the number of communities in networks by spectral methods
Can M. Le, Elizaveta Levina
Community detection is a fundamental problem in network analysis with many methods available to estimate communities. Most of these methods assume that the number of communities is…