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Algorithms and Learning for Fair Portfolio Design:
, In:
Proceedings of the 22nd ACM Conference on Economics and Computation
,
Diana, Emily
;
Dick, Travis
;
Elzayn, Hadi
... - p. 371-389 , 2021
Link:
https://dl.acm.org/doi/10.1145/3465456.3467646
RT T1 <cTitle>Proceedings of the 22nd ACM Conference on Economics and Computation</cTitle>: T1 <Title>Algorithms and Learning for Fair Portfolio Design</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3467646&Exemplar=1&LAN=DE A1 Diana, Emily A1 Dick, Travis A1 Elzayn, Hadi A1 Kearns, Michael A1 Roth, Aaron A1 Schutzman, Zachary A1 Sharifi-Malvajerdi, Saeed A1 Ziani, Juba PB ACM YR 2021 K1 algorithmic fairness K1 algorithmic game theory K1 fair finance K1 minimax fairness K1 portfolio design K1 Theory of computation K1 Design and analysis of algorithms K1 Algorithm design techniques K1 Dynamic programming K1 Applied computing K1 Law, social and behavioral sciences K1 Economics K1 Theory and algorithms for application domains K1 Algorithmic game theory and mechanism design K1 Algorithmic game theory SP 371 OP 389 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3465456.3467646 DO https://dl.acm.org/doi/10.1145/3465456.3467646 SF ELIB - SuUB Bremen
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