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DTSTAMP:20250915T235256Z
DESCRIPTION:Title: Off-Policy Confidence Interval Estimation with Confounde
 d Markov Decision Process.\n\n\n	Abstract:\n\n\nIn this talk\, we consider 
 constructing a confidence interval for a target policy’s value offline bas
 ed on pre-collected observational data in infinite horizon settings. Most 
 of the existing works assume no unmeasured variables exist that confound t
 he observed actions. This assumption\, however\, is likely to be violated 
 in real applications such as healthcare and technological industries. We s
 how that with some auxiliary variables that mediate the effect of actions 
 on the system dynamics\, the target policy’s value is identifiable in a co
 nfounded Markov decision process. Based on this result\, we develop an eff
 icient off-policy value estimator that is robust to potential model misspe
 cification and provides rigorous uncertainty quantification.\n\n\n	Speaker
 \n\n\nDr. Rui Song is a Professor of Statistics from the Department of Sta
 tistics at North Carolina State University. Her current research interests
  include Machine Learning\, Causal Inference\, Precision Health\, Financia
 l Econometrics.\n\nhttps://mcgill.zoom.us/j/83436686293?pwd=b0RmWmlXRXE3OW
 R6NlNIcWF5d0dJQT09\n\nMeeting ID: 834 3668 6293\n\nPasscode: 12345\n\n\n	\n
 		 \n			 \n		\n\n		\n			 \n	\n\n	\n		 \n	\n\n
DTSTART:20220204T203000Z
DTEND:20220204T213000Z
SUMMARY:Rui Song (North Carolina State University)
URL:/mathstat/channels/event/rui-song-north-carolina-s
 tate-university-337373
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