research
∙
06/15/2022
Summarizing Labeled Multi-Graphs
Real-world graphs can be difficult to interpret and visualize beyond a c...
share
research
∙
10/21/2019
GraphSAC: Detecting anomalies in large-scale graphs
A graph-based sampling and consensus (GraphSAC) approach is introduced t...
research
∙
11/27/2018
Adaptive-similarity node embedding for scalable learning over graphs
Node embedding is the task of extracting informative and descriptive fea...
research
∙
04/06/2018
Adaptive Bayesian Radio Tomography
Radio tomographic imaging (RTI) is an emerging technology to locate phys...
research
∙
04/05/2018
Adaptive Diffusions for Scalable Learning over Graphs
Diffusion-based classifiers such as those relying on the Personalized Pa...
research
∙
05/19/2017
Data-adaptive Active Sampling for Efficient Graph-Cognizant Classification
The present work deals with active sampling of graph nodes representing ...
research
∙
01/28/2016
