Alexandra Chouldechova
Alexandra Chouldechova
Assistant Professor of Statistics & Public Policy, Heinz College, Carnegie Mellon University
Verified email at - Homepage
Cited by
Cited by
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
A Chouldechova
Big data 5 (2), 153-163, 2017
The frontiers of fairness in machine learning
A Chouldechova, A Roth
arXiv preprint arXiv:1810.08810, 2018
Sequential selection procedures and false discovery rate control
MG G'Sell, S Wager, A Chouldechova, R Tibshirani
Journal of the Royal Statistical Society: Series B: Statistical Methodology …, 2016
A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
A Chouldechova, D Benavides-Prado, O Fialko, R Vaithianathan
Conference on Fairness, Accountability and Transparency, 134-148, 2018
Does mitigating ML's impact disparity require treatment disparity?
Z Lipton, J McAuley, A Chouldechova
Advances in neural information processing systems, 8125-8135, 2018
Generalized additive model selection
A Chouldechova, T Hastie
arXiv preprint arXiv:1506.03850, 2015
Early stem cell engraftment predicts late cardiac functional recovery: preclinical insights from molecular imaging
J Liu, KH Narsinh, F Lan, L Wang, PK Nguyen, S Hu, A Lee, L Han, ...
Circulation: Cardiovascular Imaging 5 (4), 481-490, 2012
Bias in bios: A case study of semantic representation bias in a high-stakes setting
M De-Arteaga, A Romanov, H Wallach, J Chayes, C Borgs, ...
Proceedings of the Conference on Fairness, Accountability, and Transparency …, 2019
Fairer and more accurate, but for whom?
A Chouldechova, M G'Sell
arXiv preprint arXiv:1707.00046, 2017
A snapshot of the frontiers of fairness in machine learning
A Chouldechova, A Roth
Communications of the ACM 63 (5), 82-89, 2020
Toward algorithmic accountability in public services: A qualitative study of affected community perspectives on algorithmic decision-making in child welfare services
A Brown, A Chouldechova, E Putnam-Hornstein, A Tobin, ...
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems …, 2019
What's in a Name? Reducing Bias in Bios without Access to Protected Attributes
A Romanov, M De-Arteaga, H Wallach, J Chayes, C Borgs, ...
arXiv preprint arXiv:1904.05233, 2019
Counterfactual risk assessments, evaluation, and fairness
A Coston, A Mishler, EH Kennedy, A Chouldechova
Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020
Learning under selective labels in the presence of expert consistency
M De-Arteaga, A Dubrawski, A Chouldechova
arXiv preprint arXiv:1807.00905, 2018
False discovery rate control for spatial data
A Chouldechova
PhD thesis, Stanford University, 2014
A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores
M De-Arteaga, R Fogliato, A Chouldechova
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020
Differences in search engine evaluations between query owners and non-owners
A Chouldechova, D Mease
Proceedings of the sixth ACM international conference on Web search and data …, 2013
False discovery rate control for sequential selection procedures, with application to the Lasso
MG G’Sell, S Wager, A Chouldechova, R Tibshirani
arXiv preprint arXiv:1309.5352, 2013
Safety and outcomes of mobile ECMO using a bicaval dual-stage venous catheter
HD Kanji, A Chouldechova, C Harvey, E O’dea, G Faulkner, G Peek
Asaio Journal 63 (3), 351-355, 2017
Recent advances in post-selection statistical inference
R Tibshirani, J Taylor, R Lockhart, R Tibshirani, W Fithian, J Lee, Y Sun, ...
Breiman lecture, NIPS, 2015
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