SOTAVerified

Fairness

Papers

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Showing 3901–3925 of 5676 papers

TitleStatusHype
Visualizing chest X-ray dataset biases using GANs—0
Visual Representation Learning over Latent Domains—0
Voluntary Information Disclosure in Centralized Matching: Efficiency Gains and Strategic Properties—0
VTruST: Controllable value function based subset selection for Data-Centric Trustworthy AI—0
WAFFLe: Weight Anonymized Factorization for Federated Learning—0
Walk a Mile in Their Shoes: a New Fairness Criterion for Machine Learning—0
Wasserstein-based fairness interpretability framework for machine learning models—0
Wasserstein Robust Classification with Fairness Constraints—0
WassFFed: Wasserstein Fair Federated Learning—0
Watching the Watchers: A Comparative Fairness Audit of Cloud-based Content Moderation Services—0
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts—0
Weighted Notions of Fairness with Binary Supermodular Chores—0
Weighted Sampled Split Learning (WSSL): Balancing Privacy, Robustness, and Fairness in Distributed Learning Environments—0
Welfare and Distributional Impacts of Fair Classification—0
Welfare and Fairness Dynamics in Federated Learning: A Client Selection Perspective—0
Welfare Measure for Resource Allocation with Algorithmic Implementation: Beyond Average and Max-Min—0
What About Applied Fairness?—0
What are you optimizing for? Aligning Recommender Systems with Human Values—0
What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysis—0
What do people expect from Artificial Intelligence? Public opinion on alignment in AI moderation from Germany and the United States—0
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective—0
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers—0
What Is Fairness? On the Role of Protected Attributes and Fictitious Worlds—0
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias—0
What Is the Point of Equality in Machine Learning Fairness? Beyond Equality of Opportunity—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