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Q-LEARNING WITH CENSORED DATA

We develop methodology for a multistage-decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm that is adjusted for censored data and allows a flexible number of stages. We provide finite sample b...

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Bibliografiska uppgifter
Huvudupphovsmän: Goldberg, Yair, Kosorok, Michael R.
Materialtyp: Artigo
Språk:Inglês
Publicerad: 2012
Ämnen:
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC3385950/
https://ncbi.nlm.nih.gov/pubmed/22754029
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/12-AOS968
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