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Fairness

Papers

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Showing 1851–1900 of 5676 papers

TitleStatusHype
Explainable Deep Reinforcement Learning: State of the Art and Challenges—0
Explainable Disparity Compensation for Efficient Fair Ranking—0
Contraction of Private Quantum Channels and Private Quantum Hypothesis Testing—0
Explainable Fairness in Recommendation—0
A Survey of Defenses against AI-generated Visual Media: Detection, Disruption, and Authentication—0
Continuous Multi-Link Operation: A Contention-Free Mechanism for the Unlicensed Spectrum—0
Continuous Fair SMOTE -- Fairness-Aware Stream Learning from Imbalanced Data—0
Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments—0
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects—0
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition—0
Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation—0
Explaining how your AI system is fair—0
AI based Content Creation and Product Recommendation Applications in E-commerce: An Ethical overview—0
Explaining Language Models' Predictions with High-Impact Concepts—0
Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness?—0
Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies—0
Can everyday AI be ethical. Fairness of Machine Learning Algorithms—0
Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing—0
Can Evolutionary Clustering Have Theoretical Guarantees?—0
Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making—0
Accuracy vs. Accuracy: Computational Tradeoffs Between Classification Rates and Utility—0
Contextual Thompson Sampling via Generation of Missing Data—0
Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning—0
SYNAuG: Exploiting Synthetic Data for Data Imbalance Problems—0
Exploring Accuracy-Fairness Trade-off in Large Language Models—0
Exploring Bengali Religious Dialect Biases in Large Language Models with Evaluation Perspectives—0
Exploring Bias and Prediction Metrics to Characterise the Fairness of Machine Learning for Equity-Centered Public Health Decision-Making: A Narrative Review—0
Exploring Changes in Nation Perception with Nationality-Assigned Personas in LLMs—0
Exploring Effectiveness of Explanations for Appropriate Trust: Lessons from Cognitive Psychology—0
Exploring Energy Landscapes for Minimal Counterfactual Explanations: Applications in Cybersecurity and Beyond—0
Exploring Equality: An Investigation into Custom Loss Functions for Fairness Definitions—0
Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities—0
Exploring Fairness for FAS-assisted Communication Systems: from NOMA to OMA—0
Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten—0
A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction—0
Exploring Gender Disparities in Automatic Speech Recognition Technology—0
A Suite of Fairness Datasets for Tabular Classification—0
Exploring Graph Neural Networks for Indian Legal Judgment Prediction—0
Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits—0
Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics—0
Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness—0
Appropriate Fairness Perceptions? On the Effectiveness of Explanations in Enabling People to Assess the Fairness of Automated Decision Systems—0
Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective—0
Exploring Rawlsian Fairness for K-Means Clustering—0
Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms—0
Contextual bandits with concave rewards, and an application to fair ranking—0
A Study on Fairness and Trust Perceptions in Automated Decision Making—0
Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis—0
Approximate Heavily-Constrained Learning with Lagrange Multiplier Models—0
Active Learning for Fair and Stable Online Allocations—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