conftrace_

fair machine learning

46 papers

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Co-occurring keywords

algorithmic fairness (284) bias mitigation (500) causal inference (1630) sensitive attribute (44) group fairness (158) demographic parity (75) fairness criterion (21) sample reweighting (26) counterfactual fairness (39) fair-pac learning (2)

Papers

Counterfactual Fairness with Partially Known Causal Graph NIPS 2022
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness AAAI 2022
On Learning Fairness and Accuracy on Multiple Subgroups NIPS 2022
Fair Bayes-Optimal Classifiers Under Predictive Parity NIPS 2022
Protecting the Protected Group: Circumventing Harmful Fairness AAAI 2021
Retiring Adult: New Datasets for Fair Machine Learning NIPS 2021
An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning NIPS 2021
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem NIPS 2021
FR-Train: A Mutual Information-Based Approach to Fair and Robust Training ICML 2020
Fairness in Streaming Submodular Maximization: Algorithms and Hardness NIPS 2020
Incorporating Interpretable Output Constraints in Bayesian Neural Networks NIPS 2020
Achieving Equalized Odds by Resampling Sensitive Attributes NIPS 2020
NestedVAE: Isolating Common Factors via Weak Supervision CVPR 2020
Fair Learning with Private Demographic Data ICML 2020
Fairness without Harm: Decoupled Classifiers with Preference Guarantees ICML 2019
The Fairness of Risk Scores Beyond Classification: Bipartite Ranking and the XAUC Metric NIPS 2019
Delayed Impact of Fair Machine Learning ICML 2018
Residual Unfairness in Fair Machine Learning from Prejudiced Data ICML 2018
Blind Justice: Fairness with Encrypted Sensitive Attributes ICML 2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer NIPS 2018
Counterfactual Fairness NIPS 2017