Policy Learning with Adaptively Collected Data

In a wide variety of applications, including healthcare, bidding in first price auctions, digital recommendations, and online education, it can be beneficial to learn a policy that assigns treatments to individuals based on their characteristics. The growing policy-learning literature focuses on set...

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Veröffentlicht in:	Management science 2024-08, Vol.70 (8), p.5270-5297
1. Verfasser:	Zhan, Ruohan
Format:	Artikel
Sprache:	eng
Schlagworte:	adaptive data collection Algorithms Assignment Auctions Bidding contextual bandits Data collection Decision making Distance learning Estimating techniques Health care Learning Management science minimax optimality off-line policy learning personalized decision making Process engineering Regret Weighting
Online-Zugang:	Volltext
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