Bias-inducing geometries: an exactly solvable data model with fairness implications

Type: Preprint

Publication Date: 2022-01-01

Citations: 1

DOI: https://doi.org/10.48550/arxiv.2205.15935

Locations

  • arXiv (Cornell University) - View - PDF
  • DataCite API - View

Similar Works

Action Title Year Authors
+ PDF Chat Inducing bias is simpler than you think 2022 Stefano Sarao Mannelli
Federica Gerace
Negar Rostamzadeh
Luca Saglietti
+ PDF Chat Emergent Unfairness in Algorithmic Fairness-Accuracy Trade-Off Research 2021 A. Feder Cooper
Ellen Abrams
Na Na
+ Emergent Unfairness: Normative Assumptions and Contradictions in Algorithmic Fairness-Accuracy Trade-Off Research. 2021 A. Feder Cooper
Ellen Abrams
+ Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation 2021 Agnieszka SƂowik
LĂ©on Bottou
+ PDF Chat Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors 2024 Xueying Ding
Rui Xi
Leman Akoglu
+ PDF Chat Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors 2024 Xueying Ding
Rui Xi
Leman Akoglu
+ Is it still fair? A comparative evaluation of fairness algorithms through the lens of covariate drift 2025 Oscar Blessed Deho
Michael Bewong
Selasi Kwashie
Jiuyong Li
Jixue Liu
Lin Liu
Srécko Joksimovíc
+ PDF Chat AIM: Attributing, Interpreting, Mitigating Data Unfairness 2024 Zhining Liu
Ruizhong Qiu
Zhichen Zeng
Yada Zhu
Hendrik F. Hamann
Hanghang Tong
+ Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting 2022 Prasanna Sattigeri
Soumya K. Ghosh
Inkit Padhi
Pierre Dognin
Kush R. Varshney
+ PDF Chat A Survey of Bias in Machine Learning Through the Prism of Statistical Parity 2021 Philippe Besse
Eustasio del Barrio
Paula Gordaliza
Jean-Michel LoubĂšs
Laurent Risser
+ Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning 2022 Damien Dablain
Bartosz Krawczyk
Nitesh V. Chawla
+ Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing 2019 Sanghamitra Dutta
Dennis Wei
Hazar Yueksel
Pin‐Yu Chen
Sijia Liu
Kush R. Varshney
+ Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions 2022 José P. Pombal
André F. Cruz
JoĂŁo VĂ­tor Meza Bravo
Pedro Saleiro
MĂĄrio A. T. Figueiredo
Pedro Bizarro
+ PDF Chat Is it Still Fair? A Comparative Evaluation of Fairness Algorithms through the Lens of Covariate Drift 2024 Oscar Blessed Deho
Michael Bewong
Selasi Kwashie
Jiuyong Li
Jixue Liu
Jiuyong Li
Srécko Joksimovíc
+ When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms 2023 Nataơa Krčo
Thibault Laugel
Jean–Michel Loubes
Marcin Detyniecki
+ The Measure and Mismeasure of Fairness 2018 Sam Corbett‐Davies
Sharad Goel
+ PDF Chat Moving beyond “algorithmic bias is a data problem” 2021 Sara Hooker
+ Non-Invasive Fairness in Learning through the Lens of Data Drift 2023 Ke Yang
Alexandra Meliou
+ Recovering from Biased Data: Can Fairness Constraints Improve Accuracy? 2019 Avrim Blum
Kevin Stangl
+ Fairness Sample Complexity and the Case for Human Intervention 2019 Ananth Balashankar
Alyssa Lees

Works That Cite This (0)

Action Title Year Authors

Works Cited by This (0)

Action Title Year Authors