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UID:228@isdm.umontpellier.fr
DTSTART;TZID=Europe/Paris:20240521T140000
DTEND;TZID=Europe/Paris:20240521T140000
DTSTAMP:20260825T133632Z
URL:https://isdm.umontpellier.fr/events/multiply-robust-off-policy-evaluat
 ion-and-learning-under-truncation-by-death/
SUMMARY:Multiply robust off-policy evaluation and learning under truncation
  by death
DESCRIPTION:Room 01.124\, Building 5\, St Priest campus\n\nMachine Learning
  in Montpellier\, Theory &amp\; Practice\n\nTypical off-policy evaluation 
 (OPE) and off-policy learning (OPL) are not well-defined problems under "t
 runcation by death"\, where the outcomeof interest is not defined after so
 me events\, such as death. The standard OPE no longer yields consistent es
 timators\, and the standard OPL results in suboptimal policies. In this pa
 per\, we formulate OPE and OPL using principal stratification under "trunc
 ation by death". We propose a survivor value function for a subpopulation 
 whose outcomes are always defined regardless of treatment conditions. We e
 stablish a novel identification strategy under principal ignorability\, an
 d derive the semiparametric efficiency bound of an OPE estimator. Then\, w
 e propose multiply robust estimators for OPE and OPL. We show that the pro
 posed estimators are consistent and asymptotically normal even with flexib
 le semi/nonparametric models for nuisance functions approximation. Moreove
 r\, under mild rate conditions of nuisance functions approximation\, the e
 stimators achieve the semiparametric efficiency bound. Finally\, we conduc
 t experiments to demonstrate the empirical performance of the proposed est
 imators.\n\nMachine Learning in Montpellier\, Theory &amp\; Practice
ATTACH;FMTTYPE=image/jpeg:https://isdm.umontpellier.fr/wp-content/uploads/
 2026/06/ml-mtp-gC78d5.png
CATEGORIES:ML MTP
LOCATION:Saint Priest Campus - Building 5 - Room 01.124\, 860 rue St Priest
 \, Montpellier\, 
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=860 rue St Priest\, Montpel
 lier\, ;X-APPLE-RADIUS=100;X-TITLE=Saint Priest Campus - Building 5 - Room
  01.124:geo:0,0
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