Alexandra Chouldechova

Citirano

	Sve	Od 2017.
Citati	3438	3347
H-indeks	18	18
i10-indeks	27	25

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Maria De-ArteagaAssistant Professor, University of Texas at AustinPotvrđena adresa e-pošte na utexas.edu
Aaron RothProfessor of Computer Science, University of PennsylvaniaPotvrđena adresa e-pošte na cis.upenn.edu
Zachary C. LiptonAssistant Professor of Machine Learning at CMUPotvrđena adresa e-pošte na cmu.edu
Robert TibshiraniProfessor of Biomedical Data Sciences, and of Statistics, Stanford UniversityPotvrđena adresa e-pošte na stanford.edu
rhema VaithianathanPotvrđena adresa e-pošte na aut.ac.nz
Riccardo FogliatoAmazonPotvrđena adresa e-pošte na amazon.com
Stefan WagerGraduate School of Business, Stanford UniversityPotvrđena adresa e-pošte na stanford.edu
Hanna WallachPartner Research Manager, Microsoft ResearchPotvrđena adresa e-pošte na dirichlet.net
Adam Tauman KalaiMicrosoft ResearchPotvrđena adresa e-pošte na microsoft.com
Alexey RomanovMicrosoftPotvrđena adresa e-pošte na microsoft.com
Jennifer ChayesProfessor, UC BerkeleyPotvrđena adresa e-pošte na jenniferchayes.com
Sahin Cem GeyikFacebookPotvrđena adresa e-pošte na fb.com
Edward H. KennedyAssociate Professor of Statistics & Data Science, Carnegie Mellon UniversityPotvrđena adresa e-pošte na stat.cmu.edu
Julian McAuleyProfessor, UC San DiegoPotvrđena adresa e-pošte na eng.ucsd.edu
Emily Putnam-Hornstein, PhDJohn A. Tate Distinguished Professor for Children in Need, University of North Carolina at ChapelPotvrđena adresa e-pošte na unc.edu
Trevor HastieProfessor of Statistics, Stanford UniversityPotvrđena adresa e-pošte na stanford.edu

Prati

Alexandra Chouldechova

Associate Professor of Statistics & Public Policy @ Heinz College, Carnegie Mellon University

Potvrđena adresa e-pošte na andrew.cmu.edu - Početna stranica


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments A Chouldechova Big data 5 (2), 153-163, 2017	1447	2017
The frontiers of fairness in machine learning A Chouldechova, A Roth arXiv preprint arXiv:1810.08810, 2018	289	2018
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	217	2018
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	202	2019
A snapshot of the frontiers of fairness in machine learning A Chouldechova, A Roth Communications of the ACM 63 (5), 82-89, 2020	191	2020
Does mitigating ML's impact disparity require treatment disparity? Z Lipton, J McAuley, A Chouldechova Advances in neural information processing systems 31, 2018	163	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	135	2016
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	116	2019
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	90	2020
Generalized additive model selection A Chouldechova, T Hastie arXiv preprint arXiv:1506.03850, 2015	90	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	71	2012
Fairer and more accurate, but for whom? A Chouldechova, M G'Sell arXiv preprint arXiv:1707.00046, 2017	56	2017
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	51	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	48	2020
Leveraging administrative data for bias audits: Assessing disparate coverage with mobility data for COVID-19 policy A Coston, N Guha, D Ouyang, L Lu, A Chouldechova, DE Ho Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021	29	2021
Fairness evaluation in presence of biased noisy labels R Fogliato, A Chouldechova, M G’Sell International Conference on Artificial Intelligence and Statistics, 2325-2336, 2020	28	2020
Learning under selective labels in the presence of expert consistency M De-Arteaga, A Dubrawski, A Chouldechova arXiv preprint arXiv:1807.00905, 2018	25	2018
Characterizing fairness over the set of good models under selective labels A Coston, A Rambachan, A Chouldechova International Conference on Machine Learning, 2144-2155, 2021	22	2021
Soliciting stakeholders’ fairness notions in child maltreatment predictive systems HF Cheng, L Stapleton, R Wang, P Bullock, A Chouldechova, ZSS Wu, ... Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021	17	2021
Fairness in risk assessment instruments: Post-processing to achieve counterfactual equalized odds A Mishler, EH Kennedy, A Chouldechova Proceedings of the 2021 ACM Conference on Fairness, Accountability, and …, 2021	17	2021

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