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Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data

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Published in:JMLR
Format: Online Article RSS Article
Published: 2026
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container_title JMLR
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
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genre Journal Article
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institution FRELIP
journal_source_facet JMLR
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
subject_facet Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
title Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
title_auth Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
title_full Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
title_fullStr Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
title_full_unstemmed Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
title_short Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data
title_sort efficient and robust transfer learning of optimal individualized treatment regimes with right-censored survival data
topic Artificial Intelligence & Machine Learning
Computer Science & IT
Engineering & Technology
url http://jmlr.org/papers/v26/23-0335.html