Microsoft

ECLARE: Extreme classification with label graph correlations

Deep extreme classification (XC) seeks to train deep architectures that can tag a data point with its most relevant subset of labels from an extremely large label set. The core utility of XC comes ...
Microsoft

GalaXC: Graph neural networks with labelwise attention for extreme classification

This paper develops the GalaXC algorithm for Extreme Classification, where the task is to annotate a document with the most relevant subset of labels from an extremely large label set. Extreme ...
IEEE

Can Graph Neural Networks Tackle Heterophily? Yes, With a Label-Guided Graph Rewiring Approach!

Abstract: Graph neural networks (GNNs) witness impressive performances on homophilic graphs characterized by a higher number of edges connecting nodes of similar class labels. A decline in the ...
IEEE

Semi-Supervised Graph Structure Learning via Dual Reinforcement of Label and Prior Structure

Abstract: Graph neural networks (GNNs) have achieved considerable success in dealing with graph-structured data by the message-passing mechanism. Actually, this mechanism relies on a fundamental ...