A Convex Framework for Fair Regression

7 June 2017

Hoda Heidari

Papers citing "A Convex Framework for Fair Regression"

50 / 184 papers shown

Title
Intersectional Divergence: Measuring Fairness in Regression Joe Germino Nuno Moniz Nitesh V. Chawla FaML 63 0 0 01 May 2025
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing Jitao Wang C. Shi John D. Piette Joshua R. Loftus Donglin Zeng Zhenke Wu OffRL 61 0 0 10 Jan 2025
AFed: Algorithmic Fair Federated Learning Huiqiang Chen Tianqing Zhu Wanlei Zhou Wei Zhao FedML 29 0 0 06 Jan 2025
Fair and Accurate Regression: Strong Formulations and Algorithms Anna Deza Andrés Gómez Alper Atamturk FaML 69 0 0 22 Dec 2024
Improving LLM Group Fairness on Tabular Data via In-Context Learning Valeriia Cherepanova Chia-Jung Lee Nil-Jana Akpinar Riccardo Fogliato Martín Bertrán Michael Kearns James Zou LMTD 68 0 0 05 Dec 2024
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes Jake Robertson Thorsten Schmidt Frank Hutter Noor H. Awad 33 0 0 17 Oct 2024
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction Siqi Li Qiming Wu Xin Li Di Miao Chuan Hong ... Michael Hao Chen Mengying Yan Yilin Ning M. Ong Nan Liu 31 1 0 07 Oct 2024
Achieving Fairness Across Local and Global Models in Federated Learning Disha Makhija Xing Han Joydeep Ghosh Yejin Kim FedML 35 5 0 24 Jun 2024
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas Chengyuan Deng Yiqun Duan Xin Jin Heng Chang Yijun Tian ... Kuofeng Gao Sihong He Jun Zhuang Lu Cheng Haohan Wang AILaw 38 16 0 08 Jun 2024
Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models Jiahui Wu Vanessa Frias-Martinez 19 0 0 06 Jun 2024
Fairness-Optimized Synthetic EHR Generation for Arbitrary Downstream Predictive Tasks Mirza Farhan Bin Tarek Raphael Poulain Rahmatollah Beheshti SyDa 37 0 0 04 Jun 2024
Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten Wei Qian Aobo Chen Chenxu Zhao Yangyi Li Mengdi Huai MU 34 0 0 27 May 2024
A Neurosymbolic Framework for Bias Correction in CNNs Parth Padalkar Natalia Slusarz Ekaterina Komendantskaya Gopal Gupta 32 0 0 24 May 2024
Perceptual Fairness in Image Restoration Guy Ohayon Michael Elad T. Michaeli SupR 38 1 0 22 May 2024
DemOpts: Fairness corrections in COVID-19 case prediction models N. Awasthi S. Abrar Daniel Smolyak Vanessa Frias-Martinez 21 0 0 15 May 2024
Fair Generalized Linear Mixed Models J. P. Burgard Joao Vitor Pamplona FaML 16 0 0 15 May 2024
Fairness in Reinforcement Learning: A Survey Anka Reuel Devin Ma OffRL FaML 26 4 0 11 May 2024
The Role of Learning Algorithms in Collective Action Omri Ben-Dov Jake Fawkes Samira Samadi Amartya Sanyal 24 3 0 10 May 2024
Fair Mixed Effects Support Vector Machine Joao Vitor Pamplona J. P. Burgard FaML 27 1 0 10 May 2024
Generalizing Orthogonalization for Models with Non-Linearities David Rügamer Chris Kolb Tobias Weber Lucas Kook Thomas Nagler 23 0 0 03 May 2024
Counterfactual Fairness through Transforming Data Orthogonal to Bias Shuyi Chen Shixiang Zhu FaML 16 2 0 26 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
Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency Parian Haghighat Denisa Gándara Lulu Kang Hadis Anahideh 25 0 0 23 Feb 2024
On the (In)Compatibility between Group Fairness and Individual Fairness Shizhou Xu Thomas Strohmer FaML 14 2 0 13 Jan 2024
Learning Fair Policies for Multi-stage Selection Problems from Observational Data Zhuangzhuang Jia G. A. Hanasusanto P. Vayanos Weijun Xie FaML 17 2 0 20 Dec 2023
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes Nabeel Seedat Nicolas Huynh B. V. Breugel M. Schaar 18 25 0 19 Dec 2023
Survey on AI Ethics: A Socio-technical Perspective Dave Mbiazi Meghana Bhange Maryam Babaei Ivaxi Sheth Patrik Joslin Kenfack 15 4 0 28 Nov 2023
Adversarial Reweighting Guided by Wasserstein Distance for Bias Mitigation Xuan Zhao Simone Fabbrizzi Paula Reyero Lobo Siamak Ghodsi Klaus Broelemann Steffen Staab Gjergji Kasneci 25 1 0 21 Nov 2023
Measuring and Mitigating Biases in Motor Insurance Pricing Mulah Moriah Franck Vermet Arthur Charpentier 9 1 0 20 Nov 2023
Causal Fairness-Guided Dataset Reweighting using Neural Networks Xuan Zhao Klaus Broelemann Salvatore Ruggieri Gjergji Kasneci 21 1 0 17 Nov 2023
Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models Feng Chen Liqin Wang Julie Hong Jiaqi Jiang Li Zhou 47 17 0 30 Oct 2023
fairret: a Framework for Differentiable Fairness Regularization Terms Maarten Buyl Marybeth Defrance T. D. Bie FedML 29 4 0 26 Oct 2023
Understanding Fairness Surrogate Functions in Algorithmic Fairness Wei Yao Zhanke Zhou Zhicong Li Bo Han Yong Liu 21 3 0 17 Oct 2023
Using Property Elicitation to Understand the Impacts of Fairness Regularizers Jessie Finocchiaro FaML 30 0 0 20 Sep 2023
Boosting Fair Classifier Generalization through Adaptive Priority Reweighing Zhihao Hu Yiran Xu Mengnan Du Jindong Gu Xinmei Tian Fengxiang He 22 1 0 15 Sep 2023
iBARLE: imBalance-Aware Room Layout Estimation Taotao Jing Lichen Wang Naji Khosravan Zhiqiang Wan Zachary Bessinger Zhengming Ding S. B. Kang 40 1 0 29 Aug 2023
Fair Few-shot Learning with Auxiliary Sets Song Wang Jing Ma Lu Cheng Jundong Li 40 2 0 28 Aug 2023
Fair Machine Unlearning: Data Removal while Mitigating Disparities Alexander X. Oesterling Jiaqi Ma Flavio du Pin Calmon Hima Lakkaraju FaML MU 23 19 0 27 Jul 2023
Towards A Scalable Solution for Improving Multi-Group Fairness in Compositional Classification James Atwood Tina Tian Ben Packer Meghana Deodhar Jilin Chen Alex Beutel Flavien Prost Ahmad Beirami FaML 19 1 0 11 Jul 2023
Towards Assumption-free Bias Mitigation Chia-Yuan Chang Yu-Neng Chuang Kwei-Herng Lai Xiaotian Han Xia Hu Na Zou 24 4 0 09 Jul 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 27 43 0 25 Jun 2023
The Flawed Foundations of Fair Machine Learning R. Poe Soumia Zohra El Mestari FaML 19 1 0 02 Jun 2023
Bias Mitigation Methods for Binary Classification Decision-Making Systems: Survey and Recommendations Madeleine Waller Odinaldo Rodrigues O. Cocarascu FaML AI4CE 30 2 0 31 May 2023
Monitoring Algorithmic Fairness T. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik FaML 19 6 0 25 May 2023
Mitigating Group Bias in Federated Learning: Beyond Local Fairness G. Wang Ali Payani Myungjin Lee Ramana Rao Kompella FedML 30 8 0 17 May 2023
Runtime Monitoring of Dynamic Fairness Properties T. Henzinger Mahyar Karimi Konstantin Kueffner Kaushik Mallik 29 14 0 08 May 2023
fairml: A Statistician's Take on Fair Machine Learning Modelling M. Scutari FaML 27 5 0 03 May 2023
Optimizing fairness tradeoffs in machine learning with multiobjective meta-models William La Cava FaML 6 4 0 21 Apr 2023
Counterfactually Fair Regression with Double Machine Learning Patrick Rehill FaML 4 1 0 21 Mar 2023
Travel Demand Forecasting: A Fair AI Approach Xiaojian Zhang Qian Ke Xilei Zhao AI4TS 13 2 0 03 Mar 2023