SOTAVerified

Fairness

Papers

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Showing 2901–2950 of 5676 papers

TitleStatusHype
Overcoming Challenges of Partial Client Participation in Federated Learning : A Comprehensive Review—0
Overcoming Fairness Trade-offs via Pre-processing: A Causal Perspective—0
Overcoming Representation Bias in Fairness-Aware data Repair using Optimal Transport—0
Oversampling Higher-Performing Minorities During Machine Learning Model Training Reduces Adverse Impact Slightly but Also Reduces Model Accuracy—0
Overview of the TREC 2019 Fair Ranking Track—0
Overview of the TREC 2020 Fair Ranking Track—0
P2NIA: Privacy-Preserving Non-Iterative Auditing—0
PAC-Bayesian Bound for the Conditional Value at Risk—0
Paired-Consistency: An Example-Based Model-Agnostic Approach to Fairness Regularization in Machine Learning—0
Pairwise Fairness for Ranking and Regression—0
Paper Quality Assessment based on Individual Wisdom Metrics from Open Peer Review—0
Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives—0
Parameterized Approximation for Robust Clustering in Discrete Geometric Spaces—0
Parametric Fairness with Statistical Guarantees—0
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing—0
Pareto-Optimal Fairness-Utility Amortizations in Rankings with a DBN Exposure Model—0
Pareto Optimality in No-Harm Fairness—0
Pareto-Optimal Learning from Preferences with Hidden Context—0
Pareto Pairwise Ranking for Fairness Enhancement of Recommender Systems—0
Parity-based Cumulative Fairness-aware Boosting—0
Partial Identification in Moment Models with Incomplete Data via Optimal Transport—0
Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics—0
Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning—0
Path-Specific Counterfactual Fairness—0
Path-specific Effects Based on Information Accounts of Causality—0
Path To Gain Functional Transparency In Artificial Intelligence With Meaningful Explainability—0
Patience ensures fairness—0
"Patriarchy Hurts Men Too." Does Your Model Agree? A Discussion on Fairness Assumptions—0
PC-Fairness: A Unified Framework for Measuring Causality-based Fairness—0
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review—0
Peer-to-Peer Energy Markets With Uniform Pricing: A Dynamic Operating Envelope Approach—0
Penalties and Rewards for Fair Learning in Paired Kidney Exchange Programs—0
People on Media: Jointly Identifying Credible News and Trustworthy Citizen Journalists in Online Communities—0
Perceived Fairness of the Machine Learning Development Process: Concept Scale Development—0
Perceptions of Fairness and Trustworthiness Based on Explanations in Human vs. Automated Decision-Making—0
Perceptual Fairness in Image Restoration—0
Performance Analysis and Optimisation of FFR-Aided OFDMA Networks using Channel-Aware Scheduling—0
Collaborative Channel Access and Transmission for NR Sidelink and Wi-Fi Coexistence over Unlicensed Spectrum—0
Performance of Cell-Free MmWave Massive MIMO Systems with Fronthaul Compression and DAC Quantization—0
Performative Debias with Fair-exposure Optimization Driven by Strategic Agents in Recommender Systems—0
Personalized Detection of Cognitive Biases in Actions of Users from Their Logs: Anchoring and Recency Biases—0
Personalized On-Device E-health Analytics with Decentralized Block Coordinate Descent—0
Personalizing Fairness-aware Re-ranking—0
Pessimistic Evaluation—0
PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning—0
pFedFair: Towards Optimal Group Fairness-Accuracy Trade-off in Heterogeneous Federated Learning—0
PFGuard: A Generative Framework with Privacy and Fairness Safeguards—0
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning—0
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?—0
Pilot and Data Power Control for Uplink Cell-free massive MIMO—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