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Fairness

Papers

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Showing 3801–3850 of 5676 papers

TitleStatusHype
A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms—0
Ultra-marginal Feature Importance: Learning from Data with Causal GuaranteesCode0
Causality-based Neural Network Repair—0
A Brief Guide to Designing and Evaluating Human-Centered Interactive Machine Learning—0
Demographic-Reliant Algorithmic Fairness: Characterizing the Risks of Demographic Data Collection in the Pursuit of Fairness—0
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability—0
Trinary Tools for Continuously Valued Binary Classifiers—0
The Equity Framework: Fairness Beyond Equalized Predictive Outcomes—0
Fairly Accurate: Learning Optimal Accuracy vs. Fairness Tradeoffs for Hate Speech Detection—0
Clinical trial site matching with improved diversity using fair policy learning—0
Fair Algorithm Design: Fair and Efficacious Machine Scheduling—0
Sharing the Load: Considering Fairness in De-energization Scheduling to Mitigate Wildfire Ignition Risk using Rolling Optimization—0
Breaking Fair Binary Classification with Optimal Flipping Attacks—0
Data Justice in Practice: A Guide for Developers—0
Integrating Distributed Energy Resources: Optimal Prosumer Decisions and Impacts of Net Metering Tariffs—0
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles—0
ProFairRec: Provider Fairness-aware News RecommendationCode0
Are Two Heads the Same as One? Identifying Disparate Treatment in Fair Neural NetworksCode0
Segmenting across places: The need for fair transfer learning with satellite imagery—0
Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic—0
Introducing a Framework and a Decision Protocol to Calibrate Recommender Systems—0
Reputation as insurance: how reputation moderates public backlash following a company's decision to profiteer—0
A Deep Learning-Based Approach for Cell Outage Compensation in NOMA Networks—0
Vertical Allocation-based Fair Exposure Amortizing in Ranking—0
Fault Diagnosis of Discrete-Event Systems under Non-Deterministic Observations with Output Fairness—0
Marrying Fairness and Explainability in Supervised Learning—0
Models and Mechanisms for Spatial Data Fairness—0
Tensor Completion with Provable Consistency and Fairness Guarantees for Recommender Systems—0
Differentially Private Sampling from Rashomon Sets, and the Universality of Langevin Diffusion for Convex Optimization—0
Achieving Long-Term Fairness in Sequential Decision MakingCode0
A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems—0
Adjusting for Bias with Procedural DataCode0
Optimizing generalized Gini indices for fairness in rankings—0
A Versatile Framework for Evaluating Ranked Lists in terms of Group Fairness and Relevance—0
Semi-FairVAE: Semi-supervised Fair Representation Learning with Adversarial Variational Autoencoder—0
FairRank: Fairness-aware Single-tower Ranking Framework for News Recommendation—0
Longitudinal Fairness with Censorship—0
Learning Fair Models without Sensitive Attributes: A Generative ApproachCode0
INSPIRE: Distributed Bayesian Optimization for ImproviNg SPatIal REuse in Dense WLANs—0
A Maximal Correlation Framework for Fair Machine Learning—0
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations—0
Concept Embedding Analysis: A Review—0
Searching for Network Width with Bilaterally Coupled NetworkCode0
Addressing Missing Sources with Adversarial Support-MatchingCode0
Socially Fair Mitigation of Misinformation on Social Networks via Constraint Stochastic OptimizationCode0
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning—0
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal—0
On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations—0
Representation Bias in Data: A Survey on Identification and Resolution Techniques—0
Fair Federated Learning via Bounded Group Loss—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