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Found 6 papers, 3 papers with code
Disparity, Inequality, and Accuracy Tradeoffs in Graph Neural Networks for Node Classification
Graph neural networks (GNNs) are increasingly used in critical human applications for predicting node labels in attributed graphs.
Graph Summarization via Node Grouping: A Spectral Algorithm
By initially allowing relaxed (fractional) solutions for integer maximization, we analytically expose the underlying connections to the spectral properties of the adjacency matrix.
Joint Use of Node Attributes and Proximity for Semi-Supervised Classification on Graphs
The task of node classification is to infer unknown node labels, given the labels for some of the nodes along with the network structure and other node attributes.
Iterative Classroom Teaching
We consider the machine teaching problem in a classroom-like setting wherein the teacher has to deliver the same examples to a diverse group of students.
Fake News Detection in Social Networks via Crowd Signals
The main objective of our work is to minimize the spread of misinformation by stopping the propagation of fake news in the network.
Social and Information Networks
