conftrace_

machine learning fairness

22 papers

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Also known as

ML FAIRNESS

Co-occurring keywords

demographic parity (75) algorithmic fairness (284) generative model (2892) representation learning (6206) causal inference (1630) machine learning (436) individual fairness (55) data generation (78) bias detection (419) efficient influence function (2)

Papers

Who’s the (Multi-)Fairest of Them All: Rethinking Interpolation-Based Data Augmentation Through the Lens of Multicalibration AAAI 2025
Constructing Fair Latent Space for Intersection of Fairness and Explainability AAAI 2025
Improving Subgroup Robustness via Data Selection NIPS 2024
Providing Fair Recourse over Plausible Groups AAAI 2024
Counterfactual Fairness by Combining Factual and Counterfactual Predictions NIPS 2024
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior NIPS 2024
Fair Representation Learning with Maximum Mean Discrepancy Distance Constraint (Student Abstract) AAAI 2024
Taxonomizing and Measuring Representational Harms: A Look at Image Tagging AAAI 2023
Learning Antidote Data to Individual Unfairness ICML 2023
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning NIPS 2022
On Gender Biases in Offensive Language Classification Models NAACL 2022
Fairness by “Where”: A Statistically-Robust and Model-Agnostic Bi-level Learning Framework AAAI 2022
Directional Bias Amplification ICML 2021
Uncovering Latent Biases in Text: Method and Application to Peer Review AAAI 2021
Constructing a Fair Classifier with Generated Fair Data AAAI 2021
Learning Smooth and Fair Representations AISTATS 2021
Robust Optimization for Fairness with Noisy Protected Groups NIPS 2020
Verifying Individual Fairness in Machine Learning Models UAI 2020
Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics ICML 2020
Identifying and Measuring Annotator Bias Based on Annotators’ Demographic Characteristics EMNLP 2020
On the Fairness of Disentangled Representations NIPS 2019
One-Network Adversarial Fairness AAAI 2019