FairBatch: Batch Selection for Model Fairness

3 December 2020

Papers citing "FairBatch: Batch Selection for Model Fairness"

24 / 74 papers shown

Title
A Differentiable Distance Approximation for Fairer Image Classification Nicholas Rosa Tom Drummond Mehrtash Harandi 28 0 0 09 Oct 2022
Survey on Fairness Notions and Related Tensions Guilherme Alves Fabien Bernier Miguel Couceiro K. Makhlouf C. Palamidessi Sami Zhioua FaML 46 25 0 16 Sep 2022
FedDAR: Federated Domain-Aware Representation Learning Aoxiao Zhong Hao He Zhaolin Ren Na Li Quanzheng Li OOD AI4CE 54 10 0 08 Sep 2022
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey Max Hort Zhenpeng Chen Jie M. Zhang Mark Harman Federica Sarro FaML AI4CE 38 162 0 14 Jul 2022
Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing Jiayin Jin Zeru Zhang Yang Zhou Lingfei Wu 32 13 0 22 Jun 2022
FairGrad: Fairness Aware Gradient Descent Gaurav Maheshwari Michaël Perrot FaML 49 11 0 22 Jun 2022
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks Tuan Dinh Yuchen Zeng Ruisu Zhang Ziqian Lin Michael Gira Shashank Rajput Jy-yong Sohn Dimitris Papailiopoulos Kangwook Lee LMTD 55 128 0 14 Jun 2022
Metrizing Fairness Yves Rychener Bahar Taşkesen Daniel Kuhn FaML 49 4 0 30 May 2022
Tackling Provably Hard Representative Selection via Graph Neural Networks Seyed Mehran Kazemi Anton Tsitsulin Hossein Esfandiari M. Bateni Deepak Ramachandran Bryan Perozzi Vahab Mirrokni 31 2 0 20 May 2022
Optimising Equal Opportunity Fairness in Model Training Aili Shen Xudong Han Trevor Cohn Timothy Baldwin Lea Frermann FaML 32 28 0 05 May 2022
fairlib: A Unified Framework for Assessing and Improving Classification Fairness Xudong Han Aili Shen Yitong Li Lea Frermann Timothy Baldwin Trevor Cohn VLM FaML 31 12 0 04 May 2022
Breaking Fair Binary Classification with Optimal Flipping Attacks Changhun Jo Jy-yong Sohn Kangwook Lee FaML 30 7 0 12 Apr 2022
Fair Federated Learning via Bounded Group Loss Shengyuan Hu Zhiwei Steven Wu Virginia Smith FaML FedML 29 14 0 18 Mar 2022
FORML: Learning to Reweight Data for Fairness Bobby Yan Skyler Seto N. Apostoloff FaML 29 11 0 03 Feb 2022
GALAXY: Graph-based Active Learning at the Extreme Jifan Zhang Julian Katz-Samuels Robert D. Nowak 32 31 0 03 Feb 2022
Anatomizing Bias in Facial Analysis Richa Singh P. Majumdar S. Mittal Mayank Vatsa CVBM 35 23 0 13 Dec 2021
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective Steven Euijong Whang Yuji Roh Hwanjun Song Jae-Gil Lee 29 326 0 13 Dec 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 37 36 0 04 Nov 2021
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 24 60 0 29 Oct 2021
Sample Selection for Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 21 61 0 27 Oct 2021
FairFed: Enabling Group Fairness in Federated Learning Yahya H. Ezzeldin Shen Yan Chaoyang He Emilio Ferrara A. Avestimehr FedML 33 197 0 02 Oct 2021
Fair Machine Learning under Limited Demographically Labeled Data Mustafa Safa Ozdayi Murat Kantarcioglu Rishabh K. Iyer FaML 23 3 0 03 Jun 2021
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 37 616 0 04 Oct 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 312 2,896 0 15 Sep 2016