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DTSTAMP:20250905T105831
DTSTART;TZID=America/Detroit:20250912T100000
DTEND;TZID=America/Detroit:20250912T110000
SUMMARY:Workshop / Seminar:Statistics Department Seminar Series: Irina Gaynanova\, Associate Professor\, Biostatistics\, Statistics (by courtesy)\, University of Michigan
DESCRIPTION:Abstract: Multi-view data\, where different data types are collected from the same samples\, are increasingly prevalent due to advances in omics and wearable technologies. For instance\, The Cancer Genome Atlas provides omics data from multiple platforms\, while affordable digital technologies enable the collection of multiple types of high-frequency wearable signals (e.g.\, continuous glucose monitoring (CGM)\, actigraphy) alongside tabular clinical characteristics. Integrating this multi-view data has the potential to enhance scientific insights but also presents significant analytic challenges. In this talk\, I will focus on one critical problem in multi-view representation learning: distinguishing between joint and individual signal subspaces in noisy\, high-dimensional data. I will present our recent work\, where we characterize the conditions under which these subspaces can be reliably identified\, based on an analysis of spectrum perturbations of the product of projection matrices. We develop an easy-to-use\, scalable estimation algorithm based on these insights\, which employs the rotational bootstrap and random matrix theory to partition the observed spectrum into joint\, individual\, and noise subspaces. I will illustrate this method using multi-omics data from colorectal cancer patients and a nutrigenomic study of mice. Towards the end of the talk\, I will broaden the discussion to the unique challenges of high-frequency wearable data\, where a distributional representation is more attractive than a matrix representation of derived features. I will briefly highlight some recent work in this area and conclude by outlining open problems and future research directions for multi-view representation learning.
UID:137898-21881082@events.umich.edu
URL:https://events.umich.edu/event/137898
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:seminar
LOCATION:West Hall - 340
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20250927T063318
DTSTART;TZID=America/Detroit:20250912T100000
DTEND;TZID=America/Detroit:20250912T190000
SUMMARY:Careers / Jobs:University of Michigan RE-CON Fair
DESCRIPTION:We are pleased to announce that registration is now open for the 39th Annual Michigan Real Estate Conference – RE-CON 2025\, hostedby the Weiser Center for Real Estate and the Michigan Real Estate Club.This year’s conference will bring together students\, alumni\, and industry professionals for a full day of insight\, discussion\, and connection. The day begins with a dedicated networking session\, followed by a series of expert-led panels\, covering key industry topics including REITs\, technology and innovation\, and sports development. The event will conclude with a robust Career Fair\, featuring employers from across the country\, many actively seeking Michigan talent.RE-CON continues to serveas a longstanding tradition for the University of Michigan’s growing real estate community\, offering valuable opportunities for professional development\, relationship building\, and exposure to current trends shaping the industry.We can’t wait to see you there!
UID:139176-21885007@events.umich.edu
URL:https://events.umich.edu/event/139176
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:
LOCATION:
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