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Social Norm Bias: Residual Harms of Fairness-Aware Algorithms


Aug 29, 2021
Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai

* Spotlighted at the 2021 ICML Machine Learning for Data Workshop and presented at the 2021 ICML Socially Responsible Machine Learning Workshop 

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The effect of differential victim crime reporting on predictive policing systems


Feb 04, 2021
Nil-Jana Akpinar, Maria De-Arteaga, Alexandra Chouldechova

* Conference on Fairness, Accountability, and Transparency (FAccT 2021) 

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Leveraging Expert Consistency to Improve Algorithmic Decision Support


Jan 24, 2021
Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova


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What's in a Name? Reducing Bias in Bios without Access to Protected Attributes


Apr 10, 2019
Alexey Romanov, Maria De-Arteaga, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Anna Rumshisky, Adam Tauman Kalai

* Accepted at NAACL 2019; Best Thematic Paper 

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Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting


Jan 27, 2019
Maria De-Arteaga, Alexey Romanov, Hanna Wallach, Jennifer Chayes, Christian Borgs, Alexandra Chouldechova, Sahin Geyik, Krishnaram Kenthapadi, Adam Tauman Kalai

* Accepted at ACM Conference on Fairness, Accountability, and Transparency (ACM FAT*), 2019 

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What are the biases in my word embedding?


Dec 22, 2018
Nathaniel Swinger, Maria De-Arteaga, Neil Thomas Heffernan IV, Mark DM Leiserson, Adam Tauman Kalai

* At AIES 2019: the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 

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Proceedings of NeurIPS 2018 Workshop on Machine Learning for the Developing World: Achieving Sustainable Impact


Dec 21, 2018
Maria De-Arteaga, Amanda Coston, William Herlands

* 17 papers in the proceedings. 11 additional papers were presented at the workshop but not included in the proceedings 

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Learning under selective labels in the presence of expert consistency


Jul 04, 2018
Maria De-Arteaga, Artur Dubrawski, Alexandra Chouldechova

* Presented at the 2018 Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2018) 

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Proceedings of NIPS 2017 Workshop on Machine Learning for the Developing World


Dec 12, 2017
Maria De-Arteaga, William Herlands

* 15 papers 

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Lass-0: sparse non-convex regression by local search


Feb 17, 2016
William Herlands, Maria De-Arteaga, Daniel Neill, Artur Dubrawski

* 8 pages, 1 figure. NIPS 2015 Workshop of Optimization (OPT2015) 

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Canonical Autocorrelation Analysis


Nov 19, 2015
Maria De-Arteaga, Artur Dubrawski, Peter Huggins

* 6 pages, 5 figures 

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