Enhancing Model Robustness and Fairness with Causality: A Regularization
Approach

Enhancing Model Robustness and Fairness with Causality: A Regularization Approach

3 October 2021

Papers citing "Enhancing Model Robustness and Fairness with Causality: A Regularization Approach"

10 / 10 papers shown

Title
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models Ruta Binkyte Ivaxi Sheth Zhijing Jin Mohammad Havaei Bernhard Schölkopf Mario Fritz 125 0 0 28 Feb 2025
Using Synthetic Data to Mitigate Unfairness and Preserve Privacy in Collaborative Machine Learning Chia-Yuan Wu Frank E. Curtis Daniel P. Robinson DD 38 0 0 14 Sep 2024
Achieving Fairness Across Local and Global Models in Federated Learning Disha Makhija Xing Han Joydeep Ghosh Yejin Kim FedML 37 5 0 24 Jun 2024
Fairness in Large Language Models: A Taxonomic Survey Zhibo Chu Zichong Wang Wenbin Zhang AILaw 43 32 0 31 Mar 2024
The Pursuit of Fairness in Artificial Intelligence Models: A Survey Tahsin Alamgir Kheya Mohamed Reda Bouadjenek Sunil Aryal 28 8 0 26 Mar 2024
A Survey on Fairness in Large Language Models Yingji Li Mengnan Du Rui Song Xin Wang Ying Wang ALM 49 59 0 20 Aug 2023
A Review of the Role of Causality in Developing Trustworthy AI Systems Niloy Ganguly Dren Fazlija Maryam Badar M. Fisichella Sandipan Sikdar ... Koustav Rudra Manolis Koubarakis Gourab K. Patro W. Z. E. Amri Wolfgang Nejdl CML 39 23 0 14 Feb 2023
Robustifying Sentiment Classification by Maximally Exploiting Few Counterfactuals Maarten De Raedt Fréderic Godin Chris Develder Thomas Demeester 11 1 0 21 Oct 2022
An Investigation of Why Overparameterization Exacerbates Spurious Correlations Shiori Sagawa Aditi Raghunathan Pang Wei Koh Percy Liang 149 370 0 09 May 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,203 0 23 Aug 2019