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DTSTART:20070311T020000
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DTSTAMP:20260105T093408
DTSTART;TZID=America/Detroit:20260123T100000
DTEND;TZID=America/Detroit:20260123T110000
SUMMARY:Social / Informal Gathering:La Tertulia: Spanish Coffee Hour
DESCRIPTION:Hola! ¿Cómo estás?\n\n-Practice your Spanish-speaking skills with peers & instructors in a relaxed environment. All language levels and students are welcome to join the conversation.\n\n-Come & go as you please\, stay as little or as long as you would like!\n\n-Free coffee\, tea\, light snacks\, & baked goods.\n\nThe RLL Commons is located in the center hallway of the 4th floor of the Modern Languages Building.\n\nFor more information contact Julie Harrell at (harrelju@umich.edu).
UID:143170-21892359@events.umich.edu
URL:https://events.umich.edu/event/143170
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Coffee,Undergraduate Students,Undergraduate,Study Abroad,Spanish,Spain,Social,Romance Languages And Literatures,Networking,Latin America,Languages,Language,International,Intercultural,Games,Free,Food,European,Europe,Engaged Learning,Culture,Community Engagement,Community,Central America
LOCATION:Modern Languages Building - RLL Commons, 4314 MLB
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20260116T151511
DTSTART;TZID=America/Detroit:20260123T100000
DTEND;TZID=America/Detroit:20260123T110000
SUMMARY:Workshop / Seminar:Statistics Department Seminar Series: Donglin Zeng\, Professor\, Department of Biostatistics\, University of Michigan
DESCRIPTION:Abstract:  Dynamic treatment regimens (DTRs) are sequential decisions over one or more stages that tailor treatments to individual characteristics and their intermediate outcomes. For many chronic diseases such as type 2 diabetes (T2D)\, benefit-risk tradeoff is usually an important concern for decision making in the sense that treatments with a higher benefit may lead to an increased risk of adverse outcomes (e.g.\, more intensive insulin treatment may lead to more hypoglycemia events). It is thus desirable to learn the optimal DTRs while constraining the risk to be within a tolerable range. In this talk\, we propose a learning framework for this purpose.  The framework allows the risk constraint to be imposed either at each stage for an acute risk outcome\, or cumulatively over all the stages for a long-term risk outcome. Using surrogate loss functions in empirical risk minimization\, the optimal DTRs are obtained by solving a sequence of weighted support vector machine problems in a backward fashion.  Theoretically\, we show that the estimated DTRs are Fisher consistent and we further provide the convergence rates for the value and risk functions associated with the estimated DTRs. Lastly\, the proposed method is demonstrated via simulation studies and an application to a two-stage clinical trial for treating T2D.
UID:144000-21894509@events.umich.edu
URL:https://events.umich.edu/event/144000
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:seminar
LOCATION:West Hall - 340
CONTACT:
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