Procedural Fairness

Procedural fairness in artificial intelligence focuses on ensuring that AI systems make decisions equitably across different demographic groups, mitigating biases that can lead to discriminatory outcomes. Current research emphasizes developing and evaluating fairness-aware algorithms and models, including those based on adversarial learning, data augmentation techniques like mixup, and distributionally robust optimization, across various applications like healthcare, process analytics, and recommender systems. This research is crucial for building trustworthy AI systems and addressing societal concerns about algorithmic bias, impacting both the development of ethical AI guidelines and the practical deployment of AI in sensitive domains.

489papers

Papers - Page 22

January 12, 2023

Fairly Private: Investigating The Fairness of Visual Privacy Preservation Algorithms
Sophie Noiret, Siddharth Ravi, Martin Kampel, Francisco Florez-Revuelta
Procedural Fairness Visual Privacy Privacy Preservation

January 4, 2023

On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations
Wenlong Deng, Yuan Zhong, Qi Dou, Xiaoxiao Li
Sensitive Attribute Procedural Fairness Orthogonal Basis Medical Image Classification Representation Space

January 2, 2023

Fairness Guaranteed and Auction-based x-haul and Cloud Resource Allocation in Multi-tenant O-RANs
Sourav Mondal, Marco Ruffini
Procedural Fairness Resource Allocation Network Function RAN Architecture Open Radio Access Network Auction Based Passive Optical Network

December 29, 2022

Properties of Group Fairness Metrics for Rankings
Tobias Schumacher, Marlene Lutz, Sandipan Sikdar, Markus Strohmaier
Group Fairness Fair Ranking Many Property Partial Ranking Group Fairness Metric Procedural Fairness

December 21, 2022

Consistent Range Approximation for Fair Predictive Modeling
Jiongli Zhu, Sainyam Galhotra, Nazanin Sabri, Babak Salimi
Biased Data Consistent Range Approximation Predictive Model Procedural Fairness

December 18, 2022

A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness
Tiantian Feng, Rajat Hebbar, Nicholas Mehlman, Xuan Shi, Aditya Kommineni, and Shrikanth Narayanan
Trustworthy Machine Learning Machine Learning System Procedural Fairness Machine Learning Privacy Policy Human SAFETY

December 16, 2022

Provable Fairness for Neural Network Models using Formal Verification
Giorgian Borca-Tasciuc, Xingzhi Guo, Stanley Bak, Steven Skiena
Neural Network Model Formal Proof Machine Learning Model Formal Verification Rethinking Fairness Procedural Fairness

December 13, 2022

December 9, 2022

Regulating Gatekeeper AI and Data: Transparency, Access, and Fairness under the DMA, the GDPR, and beyond
Philipp Hacker, Johann Cordes, Janina Rochon
AI Act Procedural Fairness Artificial Intelligence Transparency Index General Data Protection Regulation AI Regulation

December 7, 2022

Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations
Yuying Zhao, Yu Wang, Tyler Derr
Procedural Fairness Fairness Perception High Explainability

December 4, 2022

Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results
Nathanael Jo, Bill Tang, Kathryn Dullerud, Sina Aghaei, Eric Rice, Phebe Vayanos
Procedural Fairness Allocation Policy Resource Allocation Self Compatibility Fairness Property Fairness Metric Metric Library

December 1, 2022

Fairness in Multi-Agent Planning
Alberto Pozanco, Daniel Borrajo
Efficient Compilation Procedural Fairness Goal Oriented Task Multi Agent Planning

November 30, 2022

Welfare and Fairness in Multi-objective Reinforcement Learning
Zimeng Fan, Nianli Peng, Muhang Tian, Brandon Fain
Procedural Fairness Seller Side Outcome Fairness Vector Valued Social Welfare Multi Objective Reinforcement Learning Q Learning

November 23, 2022

November 20, 2022

Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness
Abdelrahman Zayed, Prasanna Parthasarathi, Goncalo Mordido, Hamid Palangi, Samira Shabanian, Sarath Chandar
Augmented Dataset Gender Bias Procedural Fairness Deep Learning Data Augmentation Natural Language Processing Text Classification Data Diet

Procedural Fairness

Papers - Page 22

Fairly Private: Investigating The Fairness of Visual Privacy Preservation Algorithms

On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations

Fairness Guaranteed and Auction-based x-haul and Cloud Resource Allocation in Multi-tenant O-RANs

Properties of Group Fairness Metrics for Rankings

Consistent Range Approximation for Fair Predictive Modeling

A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness

Provable Fairness for Neural Network Models using Formal Verification

Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting

FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data

Regulating Gatekeeper AI and Data: Transparency, Access, and Fairness under the DMA, the GDPR, and beyond

Fairness and Explainability: Bridging the Gap Towards Fair Model Explanations

Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results

Fairness in Multi-Agent Planning

Welfare and Fairness in Multi-objective Reinforcement Learning

On the Complexity of Finding a Diverse and Representative Committee using a Monotone, Separable Positional Multiwinner Voting Rule

Fairly Allocating Utility in Constrained Multiwinner Elections

Equality of Effort via Algorithmic Recourse

Fairness Increases Adversarial Vulnerability

Bursting the Burden Bubble? An Assessment of Sharma et al.'s Counterfactual-based Fairness Metric

Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness