The Price of Fair PCA: One Extra Dimension

31 October 2018

Papers citing "The Price of Fair PCA: One Extra Dimension"

40 / 40 papers shown

Title
StablePCA: Learning Shared Representations across Multiple Sources via Minimax Optimization Zhenyu Wang Molei Liu Jing Lei Francis Bach Zijian Guo 37 1 0 02 May 2025
Guessing Efficiently for Constrained Subspace Approximation Aditya Bhaskara S. Mahabadi Madhusudhan Reddy Pittu A. Vakilian David P. Woodruff 40 0 0 29 Apr 2025
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue Optimization Junhui Shen Aaron J. Davis Ding Lu Z. Bai 40 2 0 01 Mar 2025
MAFT: Efficient Model-Agnostic Fairness Testing for Deep Neural Networks via Zero-Order Gradient Search Zhaohui Wang Min Zhang Jingran Yang Bojie Shao Min Zhang 53 4 0 31 Dec 2024
Alpha and Prejudice: Improving $α$ -sized Worst-case Fairness via Intrinsic Reweighting Jing Li Yinghua Yao Yuangang Pan Xuanqian Wang Ivor Tsang Xiuju Fu FaML 52 0 0 05 Nov 2024
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances Jie Wang M. Boedihardjo Yao Xie 54 1 0 24 May 2024
Diversity-aware clustering: Computational Complexity and Approximation Algorithms Suhas Thejaswi Ameet Gadekar Bruno Ordozgoiti Aristides Gionis 40 1 0 10 Jan 2024
When Collaborative Filtering is not Collaborative: Unfairness of PCA for Recommendations David Liu Jackie Baek Tina Eliassi-Rad 29 0 0 15 Oct 2023
Fair principal component analysis (PCA): minorization-maximization algorithms for Fair PCA, Fair Robust PCA and Fair Sparse PCA P. Babu Petre Stoica 17 5 0 10 May 2023
Increasing Fairness via Combination with Learning Guarantees Yijun Bian Kun Zhang FaML 27 2 0 25 Jan 2023
Scalable Spectral Clustering with Group Fairness Constraints Ji Wang Ding Lu Ian Davidson Z. Bai 61 16 0 28 Oct 2022
On the Exactness of Dantzig-Wolfe Relaxation for Rank Constrained Optimization Problems Yongchun Li Weijun Xie 31 3 0 28 Oct 2022
A novel approach for Fair Principal Component Analysis based on eigendecomposition G. D. Pelegrina L. Duarte FaML 28 11 0 24 Aug 2022
Constant-Factor Approximation Algorithms for Socially Fair $k$ -Clustering Mehrdad Ghadiri Mohit Singh Santosh Vempala 21 10 0 22 Jun 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 38 78 0 06 May 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 35 15 0 23 Mar 2022
Distributionally Robust Fair Principal Components via Geodesic Descents Hieu Vu Toan M. Tran Man-Chung Yue Viet Anh Nguyen 24 14 0 07 Feb 2022
Modification-Fair Cluster Editing Vincent Froese Leon Kellerhals R. Niedermeier 38 12 0 06 Dec 2021
A Survey of Learning Criteria Going Beyond the Usual Risk Matthew J. Holland Kazuki Tanabe FaML 24 4 0 11 Oct 2021
Fairness for Image Generation with Uncertain Sensitive Attributes A. Jalal Sushrut Karmalkar Jessica Hoffmann A. Dimakis Eric Price DiffM 35 39 0 23 Jun 2021
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information Pranjal Awasthi Alex Beutel Matthaeus Kleindessner Jamie Morgenstern Xuezhi Wang FaML 54 55 0 16 Feb 2021
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification Maliha Tashfia Islam Anna Fariha A. Meliou Babak Salimi FaML 30 25 0 18 Jan 2021
Minimax Group Fairness: Algorithms and Experiments Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth FaML FedML 6 22 0 05 Nov 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 28 61 0 18 Jul 2020
Grading video interviews with fairness considerations A. Singhania Abhishek Unnam V. Aggarwal 25 6 0 02 Jul 2020
Fair clustering via equitable group representations Mohsen Abbasi Aditya Bhaskara Suresh Venkatasubramanian FaML FedML 31 86 0 19 Jun 2020
Fairness in Forecasting and Learning Linear Dynamical Systems Quan-Gen Zhou Jakub Mareˇcek Robert Shorten AI4TS 29 7 0 12 Jun 2020
Fair Principal Component Analysis and Filter Design Gad Zalcberg A. Wiesel 18 13 0 16 Feb 2020
Diversity and Inclusion Metrics in Subset Selection Margaret Mitchell Dylan K. Baker Nyalleng Moorosi Emily L. Denton Ben Hutchinson A. Hanna Timnit Gebru Jamie Morgenstern FaML 150 85 0 09 Feb 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 33 386 0 21 Jan 2020
Efficient Fair Principal Component Analysis Mohammad Mahdi Kamani Farzin Haddadpour R. Forsati M. Mahdavi 11 36 0 12 Nov 2019
A Distributed Fair Machine Learning Framework with Private Demographic Data Protection Hui Hu Yijun Liu Zhen Wang Chao Lan FaML FedML 30 25 0 17 Sep 2019
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 335 4,230 0 23 Aug 2019
Fair Kernel Regression via Fair Feature Embedding in Kernel Space Austin Okray Hui Hu Chao Lan FaML 28 4 0 04 Jul 2019
Variational Fair Clustering Imtiaz Masud Ziko Eric Granger Jing Yuan Ismail Ben Ayed 21 13 0 19 Jun 2019
Regularity Normalization: Neuroscience-Inspired Unsupervised Attention across Neural Network Layers Baihan Lin 16 2 0 27 Feb 2019
Fair k-Center Clustering for Data Summarization Matthäus Kleindessner Pranjal Awasthi Jamie Morgenstern 23 161 0 24 Jan 2019
Eliminating Latent Discrimination: Train Then Mask Soheil Ghili Ehsan Kazemi Amin Karbasi FaML 11 9 0 12 Nov 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 675 0 17 Feb 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,090 0 24 Oct 2016