Group Fairness Constraint

Group fairness constraints in machine learning aim to mitigate algorithmic bias by ensuring that models treat different demographic groups equitably, preventing discriminatory outcomes. Current research focuses on developing algorithms and model architectures (including graph neural networks and spectral clustering methods) that incorporate fairness constraints during training or post-processing, often employing techniques like Gini coefficient minimization or thresholding bias scores to achieve various fairness notions (e.g., demographic parity, equalized opportunity). This work is crucial for ensuring fairness in high-stakes applications like loan approvals and criminal justice, promoting ethical and responsible use of machine learning.

Papers

February 20, 2024

GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networks
Anuj Kumar Sirohi, Anjali Gupta, Sayan Ranu, Sandeep Kumar, Amitabha Bagchi
Graph Neural Network Group Fairness Fairness Constraint Individual Fairness Individual Perspective Group Fairness Constraint

November 23, 2023

A Unified Framework for Fair Spectral Clustering With Effective Graph Learning
Xiang Zhang, Qiao Wang
Unified Framework Spectral Clustering Graph Structure Learning Fair Clustering Group Fairness Constraint

October 9, 2023

Post-hoc Bias Scoring Is Optimal For Fair Classification
Wenlong Chen, Yegor Klochkov, Yang Liu
Fairness Constraint Fair Classification Bias Score Group Fairness Constraint

June 21, 2023

Sampling Individually-Fair Rankings that are Always Group Fair
Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis
Group Fairness Algorithmic Fairness Group Setting Fair Ranking Group Fairness Constraint

April 13, 2023

Beyond Submodularity: A Unified Framework of Randomized Set Selection with Group Fairness Constraints
Shaojie Tang, Jing Yuan
Unified Framework Submodular Maximization Subset Selection Utility Function Group Fairness Constraint Feasible Set

April 10, 2023

Achieving Long-term Fairness in Submodular Maximization through Randomization
Shaojie Tang, Jing Yuan, Twumasi Mensah-Boateng
Submodular Maximization Monotone Submodular Function Randomization Program Long Term Fairness Group Fairness Constraint

February 16, 2023

Group Fairness with Uncertainty in Sensitive Attributes
Abhin Shah, Maohao Shen, Jongha Jon Ryu, Subhro Das, Prasanna Sattigeri, Yuheng Bu, Gregory W. Wornell
Procedural Fairness High Uncertainty Anticipation Group Fairness Fairness Constraint Sensitive Attribute Fair Predictor Group Fairness Constraint

February 3, 2023

Group Fairness in Non-monotone Submodular Maximization
Jing Yuan, Shaojie Tang
Submodular Maximization Group Fairness Fairness Aware Monotone Submodular Function Group Fairness Constraint

November 30, 2022

Fair Ranking with Noisy Protected Attributes
Anay Mehrotra, Nisheeth K. Vishnoi
Fairness Constraint Protected Attribute Fair Ranking Group Fairness Constraint

November 28, 2022

FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee
Puheng Li, James Zou, Linjun Zhang
Group Fairness Fair Classification FAir Classifier Distribution Free Group Fairness Constraint

October 28, 2022

Scalable Spectral Clustering with Group Fairness Constraints
Ji Wang, Ding Lu, Ian Davidson, Zhaojun Bai
Spectral Clustering Fair Clustering Group Fairness Constraint

August 21, 2022

Individual Fairness under Varied Notions of Group Fairness in Bipartite Matching - One Framework to Approximate Them All
Atasi Panda, Anand Louis, Prajakta Nimbhorkar
New Framework Group Fairness Fairness Constraint Individual Fairness Group Fairness Constraint

June 15, 2022

Beyond Adult and COMPAS: Fairness in Multi-Class Prediction
Wael Alghamdi, Hsiang Hsu, Haewon Jeong, Hao Wang, P. Winston Michalak, Shahab Asoodeh, Flavio P. Calmon
Procedural Fairness Fairness Accuracy Older Adult Group Fairness Constraint Multi Class Classification Task Pre Trained Classifier Class Prediction Fair Classifier

March 18, 2022

Fair Federated Learning via Bounded Group Loss
Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith
Group Fairness FAIR Federated Learning Group Fairness Constraint Group Loss Fair Prediction

February 20, 2022

Bayes-Optimal Classifiers under Group Fairness
Xianli Zeng, Edgar Dobriban, Guang Cheng
Group Fairness Fair Machine Learning Fairness Accuracy Bayes Classifier Group Fairness Constraint

November 29, 2021

Contextual Combinatorial Multi-output GP Bandits with Group Constraints
Sepehr Elahi, Baran Atalar, Sevda Öğüt, Cem Tekin
Multi Armed Bandit Group Fairness Constraint Soft Set Contextual Combinatorial Gaussian Process Bandit