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  "Description": "Personalized assignment to one of many treatment arms via\nregularized and clustered joint assignment forests as described\nin Ladhania, Spiess, Ungar, and Wu (2023)\n<doi:10.48550/arXiv.2311.00577>. The algorithm pools\ninformation across treatment arms: it considers a regularized\nforest-based assignment algorithm based on greedy recursive\npartitioning that shrinks effect estimates across arms; and it\nincorporates a clustering scheme that combines treatment arms\nwith consistently similar outcomes.",
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