Application Areas

Fair Data Representation for Machine Learning at the Pareto Frontier JMLR 2023 Fair Densities via Boosting the Sufficient Statistics of Exponential Families ICML 2023 Fair Division with Prioritized Agents AAAI 2023 FaiREE: fair classification with finite-sample and distribution-free guarantee ICLR 2023 Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP EACL 2023 FAIRER: Fairness as Decision Rationale Alignment ICML 2023 FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery AISTATS 2023 FairFed: Enabling Group Fairness in Federated Learning AAAI 2023 Fair Federated Medical Image Segmentation via Client Contribution Estimation CVPR 2023 FairGBM: Gradient Boosting with Fairness Constraints ICLR 2023 Fair Generative Models via Transfer Learning AAAI 2023 Fair Graph Distillation NeurIPS 2023 Fairlearn: Assessing and Improving Fairness of AI Systems JMLR 2023 Fair learning with Wasserstein barycenters for non-decomposable performance measures AISTATS 2023 FairLISA: Fair User Modeling with Limited Sensitive Attributes Information NeurIPS 2023 Fairly Allocating Goods and (Terrible) Chores IJCAI 2023 Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach NeurIPS 2023 Fair Neighbor Embedding ICML 2023 Fairness and Accuracy under Domain Generalization ICLR 2023 Fairness and Explainability: Bridging the Gap towards Fair Model Explanations AAAI 2023 Fairness and Representation in Satellite-Based Poverty Maps: Evidence of Urban-Rural Disparities and Their Impacts on Downstream Policy IJCAI 2023 Fairness and Stability in Complex Domains IJCAI 2023 Fairness-aware class imbalanced learning on multiple subgroups UAI 2023 Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes ICLR 2023 Fairness Aware Counterfactuals for Subgroups NeurIPS 2023