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1 Ergebnisse
1
Treatment Effect Risk: Bounds and Inference:
, In:
2022 ACM Conference on Fairness, Accountability, and Transparency
,
Kallus, Nathan
- p. 213 ff. , 2022
Link:
https://dl.acm.org/doi/10.1145/3531146.3533087
RT T1 <cTitle>2022 ACM Conference on Fairness, Accountability, and Transparency</cTitle>: T1 <Title>Treatment Effect Risk: Bounds and Inference</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3533087&Exemplar=1&LAN=DE A1 Kallus, Nathan PB ACM YR 2022 K1 Conditional average treatment effect K1 Conditional value at risk K1 Debiased machine learning K1 Individual treatment effect K1 Partial identification K1 Program evaluation SP 213 ff. LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3531146.3533087 DO https://dl.acm.org/doi/10.1145/3531146.3533087 SF ELIB - SuUB Bremen
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