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DTSTART:20170312T070000
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DTSTART;TZID=America/Toronto:20170928T160000
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URL:https://uwaterloo.ca/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-susan-murphy-university
LOCATION:MC - Mathematics & Computer Building 200 University Avenue West Ro
 om: 4021 Waterloo ON N2L 3G1 Canada
SUMMARY:David Sprott Distinguished Lecture by Susan Murphy\, University of\
 nMichigan
CLASS:PUBLIC
DESCRIPTION:CHALLENGES IN DEVELOPING LEARNING ALGORITHMS TO PERSONALIZE TRE
 ATMENT\nIN REAL TIME\n\n-------------------------\n\nA formidable challeng
 e in designing sequential treatments is to\n determine when and in which 
 context it is best to deliver\ntreatments.  Consider treatment for indivi
 duals struggling with\nchronic health conditions.  Operationally designin
 g the sequential\ntreatments involves the construction of decision rules t
 hat input\ncurrent context of an individual and output a recommended treat
 ment.\n  That is\, the treatment is adapted to the individual's context\;
  the\ncontext may include  current health status\, current level of socia
 l\nsupport and current level of adherence for example.  Data sets on\nind
 ividuals with records of time-varying context and treatment\ndelivery can 
 be used to inform the construction of the decision rules.\n   There is m
 uch interest in personalizing the decision rules\,\nparticularly in real t
 ime as the individual experiences sequences of\ntreatment.   Here we disc
 uss our work in designing  online \"bandit\"\nlearning algorithms for use
  in personalizing mobile health\ninterventions. 
DTSTAMP:20260410T173223Z
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