Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

1 July 2017

Papers citing "Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations"

50 / 95 papers shown

Title
FairZK: A Scalable System to Prove Machine Learning Fairness in Zero-Knowledge Tianyu Zhang Shen Dong O. Deniz Kose Yanning Shen Wenjie Qu FaML 58 0 0 12 May 2025
Causally Fair Node Classification on Non-IID Graph Data Yucong Dai Lu Zhang Yaowei Hu Susan Gauch Yongkai Wu FaML 50 0 0 03 May 2025
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Zihan Chen Xingbo Fu Yushun Dong Jundong Li Cong Shen FedML 69 0 0 29 Apr 2025
Fair Text Classification via Transferable Representations Thibaud Leteno Michael Perrot Charlotte Laclau Antoine Gourru Christophe Gravier FaML 88 0 0 10 Mar 2025
Graph Condensation: A Survey Xin Gao Junliang Yu Wei Jiang Tong Chen Wentao Zhang Hongzhi Yin DD 106 19 0 28 Jan 2025
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage Ying Song Balaji Palanisamy 85 0 0 28 Jan 2025
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing Jitao Wang C. Shi John D. Piette Joshua R. Loftus Donglin Zeng Zhenke Wu OffRL 64 0 0 10 Jan 2025
Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion Abdullah Alchihabi Yuhong Guo DiffM 30 0 0 03 Jan 2025
Multi-Output Distributional Fairness via Post-Processing Gang Li Qihang Lin Ayush Ghosh Tianbao Yang 55 0 0 31 Aug 2024
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning Qi Qi Quanqi Hu Qihang Lin Tianbao Yang 49 1 0 09 Jun 2024
Reproducibility study of FairAC Gijs de Jong Macha J. Meijer Derck W. E. Prinzhorn Harold Ruiter 34 0 0 05 Jun 2024
Fair MP-BOOST: Fair and Interpretable Minipatch Boosting Camille Olivia Little Genevera I. Allen 30 0 0 01 Apr 2024
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes Jinwon Sohn Qifan Song Guang Lin FaML 42 1 0 10 Nov 2023
FairVision: Equitable Deep Learning for Eye Disease Screening via Fair Identity Scaling Yan Luo Muhammad Osama Khan Yu Tian Minfei Shi Zehao Dou T. Elze Yi Fang Mengyu Wang 17 7 0 03 Oct 2023
Should We Attend More or Less? Modulating Attention for Fairness A. Zayed Gonçalo Mordido Samira Shabanian Sarath Chandar 40 10 0 22 May 2023
Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection Shadi Iskander Kira Radinsky Yonatan Belinkov 49 17 0 17 May 2023
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach Zhimeng Jiang Xiaotian Han Hongye Jin Guanchu Wang Rui Chen Na Zou Xia Hu 17 13 0 06 Mar 2023
Fair Decision-making Under Uncertainty Wenbin Zhang Jeremy C. Weiss 45 38 0 29 Jan 2023
RISE: Robust Individualized Decision Learning with Sensitive Variables Xiaoqing Ellen Tan Zhengling Qi C. Seymour Lu Tang OffRL 26 8 0 12 Nov 2022
Improving Fairness in Image Classification via Sketching Ruichen Yao Ziteng Cui Xiaoxiao Li Lin Gu 38 15 0 31 Oct 2022
A Differentiable Distance Approximation for Fairer Image Classification Nicholas Rosa Tom Drummond Mehrtash Harandi 26 0 0 09 Oct 2022
Improving Data-Efficient Fossil Segmentation via Model Editing Indu Panigrahi Ryan Manzuk A. Maloof Ruth C. Fong 35 1 0 08 Oct 2022
Matching Consumer Fairness Objectives & Strategies for RecSys Michael D. Ekstrand M. S. Pera FaML 32 3 0 06 Sep 2022
A Realism Metric for Generated LiDAR Point Clouds Larissa T. Triess Christoph B. Rist David Peter J. Marius Zöllner 3DPC 37 8 0 31 Aug 2022
FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning Siyi Du Ben Hers Nourhan Bayasi Ghassan Hamarneh Rafeef Garbi 29 21 0 22 Aug 2022
Multiple Attribute Fairness: Application to Fraud Detection Meghanath Macha Yadagiri S. Ravindran Deepak Pai A. Narang V. Srivastava 35 1 0 28 Jul 2022
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization Bang An Zora Che Mucong Ding Furong Huang 24 31 0 26 Jun 2022
FairNorm: Fair and Fast Graph Neural Network Training Öykü Deniz Köse Yanning Shen AI4CE 21 4 0 20 May 2022
Learning Disentangled Textual Representations via Statistical Measures of Similarity Pierre Colombo Guillaume Staerman Nathan Noiry Pablo Piantanida FaML DRL 38 22 0 07 May 2022
FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons Xuanqi Gao Juan Zhai Shiqing Ma Chao Shen Yufei Chen Qianqian Wang 34 37 0 06 Apr 2022
Longitudinal Fairness with Censorship Wenbin Zhang Jeremy C. Weiss 25 40 0 30 Mar 2022
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning Natalie Dullerud Karsten Roth Kimia Hamidieh Nicolas Papernot Marzyeh Ghassemi 37 15 0 23 Mar 2022
Robustness and Adaptation to Hidden Factors of Variation William Paul Philippe Burlina 29 0 0 03 Mar 2022
Fairness-aware Adversarial Perturbation Towards Bias Mitigation for Deployed Deep Models Zhibo Wang Xiaowei Dong Henry Xue Zhifei Zhang Weifeng Chiu Tao Wei Kui Ren AAML 13 71 0 03 Mar 2022
Distributionally Robust Fair Principal Components via Geodesic Descents Hieu Vu Toan M. Tran Man-Chung Yue Viet Anh Nguyen 27 14 0 07 Feb 2022
Learning Fair Node Representations with Graph Counterfactual Fairness Jing Ma Ruocheng Guo Mengting Wan Longqi Yang Aidong Zhang Jundong Li FaML 12 79 0 10 Jan 2022
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach Zhao Wang Kai Shu A. Culotta OOD 21 14 0 03 Oct 2021
Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models Yunhan Zheng Shenhao Wang Jinhuan Zhao HAI 24 27 0 25 Sep 2021
Quantifying point cloud realism through adversarially learned latent representations Larissa T. Triess David Peter Stefan A. Baur J. Marius Zöllner 3DPC 34 2 0 24 Sep 2021
Adversarial Representation Learning With Closed-Form Solvers Bashir Sadeghi Lan Wang Vishnu Boddeti 37 5 0 12 Sep 2021
Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks Xudong Shen Yongkang Wong Mohan S. Kankanhalli FaML 37 20 0 01 Sep 2021
Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning Sen Cui Weishen Pan Jian Liang Changshui Zhang Fei-Yue Wang FedML 28 84 0 19 Aug 2021
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks Yushun Dong Ninghao Liu B. Jalaeian Jundong Li 33 118 0 11 Aug 2021
Impossibility results for fair representations Tosca Lechner Shai Ben-David Sushant Agarwal Nivasini Ananthakrishnan FaML 24 14 0 07 Jul 2021
Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics Paula Czarnowska Yogarshi Vyas Kashif Shah 21 104 0 28 Jun 2021
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation Agnieszka Słowik Léon Bottou FaML 45 19 0 17 Jun 2021
Fairness-Aware Node Representation Learning Öykü Deniz Köse Yanning Shen 32 22 0 09 Jun 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 27 47 0 04 Jun 2021
Personalized Counterfactual Fairness in Recommendation Yunqi Li Hanxiong Chen Shuyuan Xu Yingqiang Ge Yongfeng Zhang FaML OffRL 29 142 0 20 May 2021
Towards Equity and Algorithmic Fairness in Student Grade Prediction Weijie Jiang Z. Pardos FaML 33 47 0 14 May 2021