SOTAVerified

Fairness

Papers

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Showing 3301–3325 of 5676 papers

TitleStatusHype
Social Diversity Reduces the Complexity and Cost of Fostering Fairness—0
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without DemographicsCode0
On the Alignment of Group Fairness with Attribute Privacy—0
A Fair Loss Function for Network PruningCode0
FairMILE: Towards an Efficient Framework for Fair Graph Representation LearningCode0
Mitigating Urban-Rural Disparities in Contrastive Representation Learning with Satellite ImageryCode0
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders—0
Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN—0
Scalar Invariant Networks with Zero Bias—0
On Penalization in Stochastic Multi-armed Bandits—0
On Energy Efficiency and Fairness Maximization in RIS-Assisted MU-MISO mmWave Communications—0
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition—0
A Survey on Preserving Fairness Guarantees in Changing Environments—0
Early Diagnosis of Chronic Obstructive Pulmonary Disease from Chest X-Rays using Transfer Learning and Fusion Strategies—0
RISE: Robust Individualized Decision Learning with Sensitive VariablesCode0
Long bet will lose: demystifying seemingly fair gambling via two-armed Futurity bandit—0
Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models—0
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes—0
Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey—0
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model ControlCode0
Fairness and bias correction in machine learning for depression prediction: results from four study populationsCode0
Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness—0
Discrimination and Class Imbalance Aware Online Naive Bayes—0
Towards Algorithmic Fairness in Space-Time: Filling in Black Holes—0
Reinforcement Learning with Stepwise Fairness Constraints—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)99.86—Unverified
21D-CSNNPredictive Equality (age)97.8—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)96.87—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.97—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.45—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.68—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)99.31—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)0.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)6.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)1.96—Unverified