2019
Compositional Fairness Constraints for Graph Embeddings
ICML 2019oral
Learning high-quality node embeddings is a key building block for machine learning models that operate on graph data, such as social networks and recommender systems. However, existing graph embedding techniques are unable to cope with fairness constraints, e.g., ensuring that the learned representa…