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Planning to Fairly Allocate: Probabilistic Fairness in the ..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Herlihy, Christine ; Prins, Aviva ; Srinivasan, Aravind. - p. 732-740 , 2023

Link: https://dl.acm.org/doi/10.1145/3580305.3599467

RT 
T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3599467&Exemplar=1&LAN=DE
				
A1 Herlihy, Christine
A1 Prins, Aviva
A1 Srinivasan, Aravind
A1 Dickerson, John P.
PB ACM
YR 2023
K1 collapsing multi-armed bandits
K1 healthcare
K1 intervention planning
K1 pomdp
K1 probabilistic fairness
K1 resource allocation
K1 restless multi-armed bandits
K1 sequential decision making
K1 whittle index
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Partially-observable Markov decision processes
K1 Artificial intelligence
K1 Planning and scheduling
K1 Multi-agent planning
K1 Applied computing
K1 Life and medical sciences
K1 Health care information systems
SP 732
OP 740
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599467
DO https://dl.acm.org/doi/10.1145/3580305.3599467
SF ELIB - SuUB Bremen

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