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Fairness

3,511 papers

Papers per year

251
692
'20
'25

Papers

(Almost Full) EFX for Three (and More) Types of Agents AAAI 2025
Reducing Leximin Fairness to Utilitarian Optimization AAAI 2025
Active Fourier Auditor for Estimating Distributional Properties of ML Models AAAI 2025
Fairness Shields: Safeguarding against Biased Decision Makers AAAI 2025
Robust Logit Adjustment for Learning with Long-Tailed Noisy Data AAAI 2025
Proportionally Fair Matching via Randomized Rounding AAAI 2025
Maintaining Fairness in Logit-based Knowledge Distillation for Class-Incremental Learning AAAI 2025
Auditing and Enforcing Conditional Fairness via Optimal Transport AAAI 2025
Who’s the (Multi-)Fairest of Them All: Rethinking Interpolation-Based Data Augmentation Through the Lens of Multicalibration AAAI 2025
FedAA: A Reinforcement Learning Perspective on Adaptive Aggregation for Fair and Robust Federated Learning AAAI 2025
Equal Merit Does Not Imply Equality: Discrimination at Equilibrium in a Hiring Market with Symmetric Agents AAAI 2025
Metric-Agnostic Continual Learning for Sustainable Group Fairness AAAI 2025
Local Causal Discovery for Structural Evidence of Direct Discrimination AAAI 2025
Sequential Conditional Transport on Probabilistic Graphs for Interpretable Counterfactual Fairness AAAI 2025
Assessing Modality Bias in Video Question Answering Benchmarks with Multimodal Large Language Models AAAI 2025
Fair Federated Survival Analysis AAAI 2025
Can Private Machine Learning Be Fair? AAAI 2025
Boosting Test Performance with Importance Sampling--a Subpopulation Perspective AAAI 2025
Stop Diverse OOD Attacks: Knowledge Ensemble for Reliable Defense AAAI 2025
Knockoffs Inference for Partially Linear Models with Automatic Structure Discovery AAAI 2025
LoGoFair: Post-Processing for Local and Global Fairness in Federated Learning AAAI 2025
Towards Macro-AUC Oriented Imbalanced Multi-Label Continual Learning AAAI 2025
Navigating Towards Fairness with Data Selection AAAI 2025
Causally Consistent Normalizing Flow AAAI 2025
Investigating the Security Threat Arising from “Yes-No” Implicit Bias in Large Language Models AAAI 2025