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DTSTAMP:20251001T125501
DTSTART;TZID=America/Detroit:20251111T123000
DTEND;TZID=America/Detroit:20251111T133000
SUMMARY:Social / Informal Gathering:Pause Café: French Conversation Hour
DESCRIPTION:-Enjoy coffee\, tea\, and snacks while improving your French skills! \n\n-Chat for 10 minutes or the entire hour. All language levels are welcome.\n\nThe RLL Commons is located in the center hallway of the 4th floor of the Modern Languages Building. \n\nFor more information contact Alan Ames at (alanames@umich.edu).
UID:138670-21883575@events.umich.edu
URL:https://events.umich.edu/event/138670
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Food,Language,Intercultural,Interactive,In Person,Humanities,Global,Games,French,Free,Discussion,Culture,Community,Coffee,Multicultural,Networking,Romance Languages And Literatures,Social,Talk
LOCATION:Modern Languages Building - RLL Commons, 4314 MLB
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20251126T123128
DTSTART;TZID=America/Detroit:20251111T130000
DTEND;TZID=America/Detroit:20251111T150000
SUMMARY:Careers / Jobs:AmplifyME! Banking Technical Workshop
DESCRIPTION:The AmplifyME Banking Technical Workshopgives students the chance to experience life as ajunior GCIB analyst and gain the technical skillsneeded to succeed in investment banking.What to expect: Hands-On Training: Work on real-worldtransactions and company case studies.• Key Technical Skills: Learn Excel modelling\,three-statement analysis\, and core valuationmethods such as DCF and ComparableCompany Analysis.• Step-by-Step Support: Expert trainerguidance\, easy-to-follow videos\, and color codedmaterials make the session accessibleto everyone\, no matter your background.• Career Insights: Understand what recruiterslook for in technical assessments and howto stand outin the Bank of Americarecruitment process.
UID:141331-21888645@events.umich.edu
URL:https://events.umich.edu/event/141331
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:
LOCATION:
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20251030T101626
DTSTART;TZID=America/Detroit:20251111T130000
DTEND;TZID=America/Detroit:20251111T150000
SUMMARY:Lecture / Discussion:Conformally Robust Decision Making
DESCRIPTION:Black-box machine learning models are seeing increasing deployment in safety-critical settings\, such as in autonomous vehicles and healthcare settings. This coupling increases the need to have reliable uncertainty quantification. Traditional methods for such estimation\, however\, require distributional assumptions that are incompatible with these modern black-box estimators. In their place\, post-hoc\, distribution-free methods of uncertainty quantification have arisen. Among these is ``conformal prediction.'' At its core\, conformal prediction performs uncertainty quantification by replacing model point predictions with ``prediction regions\,'' subsets of the output space whose shape and size are defined to guarantee coverage of the truth with some user-specified probability.\n\nDespite such guarantees\, these implicitly defined predictions regions do not directly lend themselves to practical use\; while researchers professed their supposed utility\, their downstream use was not immediately obvious. In this thesis\, we propose and develop one such use: model-based decision-making. We demonstrate that conformal prediction can be integrated into a variety of decision-making pipelines\, from single-step predict-then-optimize problems to model-based LQR control\, and consequently enable guarantees on suboptimality that otherwise cannot be established.\n\nWe develop this conformal decision-making framework over three works. In the first\, we focus on the development of conformal prediction in the space of scientific inquiry: here\, decisions are often framed as hypothesis testing of parameter values. Increasingly common in certain domains\, such as astrophysics and neuroscience\, is the use approximate variational inference to do such parameter estimation\, due to the large scale at which such estimation is to be performed. Amortized variational inference produces a posterior approximation that can be rapidly computed given any new observation. Unfortunately\, there are few guarantees about the quality of these approximate posteriors. We propose Conformalized Amortized Neural Variational Inference (CANVI)\, a procedure that is scalable\, easily implemented\, and provides guaranteed marginal coverage. Given a collection of candidate amortized posterior approximators\, CANVI constructs conformalized predictors based on each candidate\, compares the predictors using a metric known as predictive efficiency\, and returns the most efficient predictor. \n\nIn the next work\, we generalize the setting for such robust decision-making\, expanding from scientific parameter testing to a more general space of ``predict-then-optimize'' problems. As in standard decision-making formulations\, these problems frame the decision-making task as a parametric optimization problem. The unique aspect here\, however\, is that the parameters of the problem are not revealed to the decision-maker. As a result\, the decision-maker is forced to estimate the unknown parameters and optimize their decision against this surrogate objective\, hence the given name: the estimation is performed by ``predicting'' the parameters with an upstream model. In the nominal approach\, the parameters predicted by the upstream model are assumed to precisely coincide with the true\, unknown parameters\; this approach of specification\, however\, fails to have any formal guarantees on the resulting decision. Towards this end\, we develop a robust analog of this nominal problem formulation\, called ``Conformal Predict-Then-Optimize'' (CPO)\, from which suboptimality guarantees can be established. We then demonstrate how a simple\, residual-based score results in overly conservative decision-making and propose an alternative score that produces structured\, non-convex prediction regions and\, in turn\, more informative decisions. \n\nFinally\, we demonstrate the generality of the proposed conformal predict-then-optimize decision-making framework. In particular\, we demonstrate that CPO can be extended to a recently proposed extension to conformal prediction in which the scalar score function is replaced with an analogous vector score and the quantile threshold by a quantile envelope. We similarly demonstrate that CPO naturally lends itself to extension to model-based robust control applications. We\, thus\, develop extensions across these two applications and then demonstrate the consistent empirical improvements produced in each.
UID:141318-21888574@events.umich.edu
URL:https://events.umich.edu/event/141318
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Dissertation
LOCATION:West Hall - 438
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20251023T135337
DTSTART;TZID=America/Detroit:20251111T130000
DTEND;TZID=America/Detroit:20251111T170000
SUMMARY:Recreational / Games:CVGA Video Game Challenge
DESCRIPTION:Join the Video Game Challenge in the CVGA (Computer & Video Game Archive) Room 4041\, Shapiro Library—featuring classic favorites Katamari Damacy and Bubble Bobble!  Test your skills\, compete for the highest score\, and see your name rise on the CVGA scoreboard.\n\nTop scorers for each game will win a prize! 🏆\n\nThe challenge runs through Friday\, November 14th.  Stop by the CVGA front desk for details and to join the fun!
UID:141063-21888068@events.umich.edu
URL:https://events.umich.edu/event/141063
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Arts For All,Free,Games,Video Games
LOCATION:Shapiro Library - Room 4041
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20250903T151824
DTSTART;TZID=America/Detroit:20251111T130000
DTEND;TZID=America/Detroit:20251111T140000
SUMMARY:Social / Informal Gathering:Kreativwerkstatt
DESCRIPTION:Chat in German and express yourself creatively. Crafting\, coloring\, painting\, drawing\, knitting\, sewing\, crochet\, embroidery\, origami? You will combine speaking German\, any level welcome\, beginners included\, and creatively expressing yourself. You are encouraged to bring your own materials or (ongoing) projects\, but we will also provide some materials and prompts each week. Contact Laura Okkema (lokkema@umich.edu) or Iris Zapf-Garcia (iriszaga@umich.edu.) with questions.
UID:138776-21883902@events.umich.edu
URL:https://events.umich.edu/event/138776
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Germanic Languages And Literatures
LOCATION:Modern Languages Building - 3030 - Slavic Seminar Room
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20251205T134357
DTSTART;TZID=America/Detroit:20251111T130000
DTEND;TZID=America/Detroit:20251111T150000
SUMMARY:Social / Informal Gathering:LGBTea
DESCRIPTION:Sip\, spill\, or just chill—we're taking a break! Bookmark your spot\, close that laptop\, and join us at Spectrum Center for some LGBTea. Relax with some tabletop and Switch games\, activities\, community\, and more. Then leave recharged and ready to take on the rest of your day. Your body and mind will thank you later.\n\n- October 1\, 2:30-4:30 pm\, Spectrum Center\n- [LGBTea x CommuniTea] November 11\, 2025\, 1:00-3:00 pm\, Trotter Multicultural Center\, Sankofa Lounge\n- [Winter Wellness Edition with GILE] December 10\, 2:30-4:30 pm\, Spectrum Center\n\nMORE SPECTRUM CENTER EVENTS\nhttps://spectrumcenter.umich.edu/events
UID:136289-21878723@events.umich.edu
URL:https://events.umich.edu/event/136289
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Queer Trans Indigenous People of Color-QTIPOC,LGBTQ Graduate Student,LGBT
LOCATION:Trotter Multicultural Center - Sankofa Lounge
CONTACT:
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