Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Alexandra Chouldechova"'
Autor:
Tianyu Zhang, Geyu Zhou, Lambertus Klei, Peng Liu, Alexandra Chouldechova, Hongyu Zhao, Kathryn Roeder, Max G’Sell, Bernie Devlin
Publikováno v:
HGG Advances, Vol 5, Iss 2, Pp 100280- (2024)
Summary: Polygenic scores (PGSs) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. O
Externí odkaz:
https://doaj.org/article/897e701c2de84722aba1bb15d9eabcef
Autor:
Lingwei Cheng, Alexandra Chouldechova
Algorithm aversion occurs when humans are reluctant to use algorithms despite their superior performance. Studies show that giving users outcome control by providing agency over how models' predictions are incorporated into decision-making mitigates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c7b2ea9fd49ddfaf8e42d0f8fd924f27
http://arxiv.org/abs/2303.12896
http://arxiv.org/abs/2303.12896
Autor:
Ephraim O’dea, Samantha Harris-Fox, Juan J. Ronco, Chris Harvey, Sonny Thiara, Hussein D. Kanji, Alexandra Chouldechova, Giles J. Peek, Constantin Shuster
Publikováno v:
Journal of Critical Care. 66:26-30
Purpose Quality of life (QoL) outcomes of patients treated with extracorporeal membrane oxygenation (ECMO) for acute respiratory distress syndrome (ARDS) have been conflicting. This study reports on QoL outcomes for a broad group of ARDS patients man
Autor:
Logan Stapleton, Min Hun Lee, Diana Qing, Marya Wright, Alexandra Chouldechova, Ken Holstein, Zhiwei Steven Wu, Haiyi Zhu
Child welfare agencies across the United States are turning to data-driven predictive technologies (commonly called predictive analytics) which use government administrative data to assist workers' decision-making. While some prior work has explored
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a92b75a237c57da40c492e1c78cfa5c5
http://arxiv.org/abs/2205.08928
http://arxiv.org/abs/2205.08928
Autor:
Aaron Roth, Alexandra Chouldechova
Publikováno v:
Communications of the ACM. 63:82-89
A group of industry, academic, and government experts convene in Philadelphia to explore the roots of algorithmic bias.
Publikováno v:
SSRN Electronic Journal.
Autor:
Lingwei Cheng, Alexandra Chouldechova
Algorithmic risk assessment tools are now commonplace in public sector domains such as criminal justice and human services. These tools are intended to aid decision makers in systematically using rich and complex data captured in administrative syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0739514c3a03357ce16c228e924a2198
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031197772
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5bd5a84307ab3bef3695ecd6c1fbc12
https://doi.org/10.1007/978-3-031-19778-9_17
https://doi.org/10.1007/978-3-031-19778-9_17
Autor:
Paige Bullock, Zhiwei Steven Wu, Logan Stapleton, Ruiqi Wang, Haiyi Zhu, Hao Fei Cheng, Alexandra Chouldechova
Publikováno v:
CHI
Recent work in fair machine learning has proposed dozens of technical definitions of algorithmic fairness and methods for enforcing these definitions. However, we still lack an understanding of how to develop machine learning systems with fairness cr
Publikováno v:
FAccT
In domains such as criminal justice, medicine, and social welfare, decision makers increasingly have access to algorithmic Risk Assessment Instruments (RAIs). RAIs estimate the risk of an adverse outcome such as recidivism or child neglect, potential