Fairness-aware Learning through Regularization Approach

Correcting Popularity Bias by Enhancing Recommendation Neutrality

Fairness-aware Classifier with Prejudice Remover Regularizer

Consideration on Fairness-aware Data Mining

Efficiency Improvement of Neutrality-Enhanced Recommendation

Future Directions of Fairness-Aware Data Mining: Recommendation, Causality, and Theoretical Aspects

Model-based Approaches for Independence-Enhanced Recommendation

ICML2015読み会 資料