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DTSTAMP:20240411T115518
DTSTART;TZID=America/Detroit:20240529T113000
DTEND;TZID=America/Detroit:20240529T133000
SUMMARY:Lecture / Discussion:Statistics in the Modern Era: High Dimensions\, Decision-Making\, and Privacy
DESCRIPTION:Abstract: The rapid growth of Artificial Intelligence (AI) and the abundance of data collection from edge devices like cell phones\, personal computers\, and smartwatches\, have put the privacy of personal data at risk. Therefore\, differential privacy (DP)\, a mathematical framework that guarantees data privacy protection by ensuring similar output irrespective of the presence or absence of an individual in the database\, has emerged as one of the leading research areas in the landscape of modern AI. Although\, DP algorithms have been used in several machine learning problems including risk minimization\, density estimation\, and hypothesis testing\, theoretical investigation of model selection under the DP framework remained somewhat scarce for high-dimensional data. This is concerning as model selection methods are heavily used in high-dimensional genetic data containing sensitive information that may compromise patient’s privacy\, thereby hindering data sharing and delaying scientific advancements. In this talk\, we propose a differentially private algorithm for model selection under the high-dimensional sparse regression setup. We adopt the well-known exponential mechanism for designing a sampling scheme that can identify the true set of features under desirable condition on the signal. In fact\, under low privacy regime\, we show that the minimum signal strength requirement exactly matches with the requirement under non-private setting. Moreover\, to achieve computational expediency over the intractable exponential mechanism\, we design a Metropolis-Hastings chain that quickly mixes to the target distribution to generate private estimates of the model. Therefore\, our research provides the first private algorithm for model selection that provably achieves high utility along with computational efficiency\, allowing efficient sharing of scientific discoveries to a broader community to practice open science.
UID:121365-21846456@events.umich.edu
URL:https://events.umich.edu/event/121365
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Dissertation
LOCATION:West Hall - 438
CONTACT:
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DTSTAMP:20240508T115853
DTSTART;TZID=America/Detroit:20240529T120000
DTEND;TZID=America/Detroit:20240529T130000
SUMMARY:Performance:Community Keys
DESCRIPTION:From May 1 to June 21\, painted pianos by University of Michigan students bring Ann Arbor public spaces to life with impromptu performances throughout Ann Arbor.\n\nThe project’s grand finale piano trio performance is at 8:15PM on June 21 at Top of the Park for a Make Music Day community concert.\n\nScheduled University of Michigan student performances occur at 12:00pm on Wednesdays and Saturdays at the following locations:\n \nSaturday\, May 4: Michigan Theater – Trenton Chang\nWednesday\, May 8: Shapiro Undergraduate Library – Matthew Osterholzer\nSaturday\, May 11: Ann Arbor Farmers Market – Trenton Chang\nWednesday\, May 15: Michigan Theater – Mira Walker\nSaturday\, May 18: Ann Arbor Farmers Market – Mark Zhu\nWednesday\, May 22: Shapiro Undergraduate Library – Cindy Lee\nSaturday\, May 25: Michigan Theater – Cindy Lee\nWednesday\, May 29: Michigan Theater – Matthew Osterholzer\nSaturday\, June 1: Ann Arbor Farmers Market – Max Zelle\nWednesday\, June 5: Shapiro Undergraduate Library – Mira Walker\nSaturday\, June 8: Ann Arbor Farmers Market – Regina Arriola\nWednesday\, June 12: Shapiro Undergraduate Library – Regina Arriola\nSaturday\, June 15: Ann Arbor Farmers Market – Mark Zhu\nWednesday\, June 19: Michigan Theater – Max Zelle\n\nThe Community Keys project was proposed by Ashley Gray\, Sophomore in the School of Kinesiology\, and is supported through the U-M Arts Initiative’s Projects in Partnership (PiP) (*formerly Collaborative Projects) funding program\, which supports large-scale projects that activate the campus and local community.\n\nPresented by Arts Initiative\, A2SF\, Ann Arbor Farmers Market\, Michigan Theater\, Michigan Libraries\, with additional support from Louise and Andrew Chang.
UID:122031-21848021@events.umich.edu
URL:https://events.umich.edu/event/122031
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Art,Concert,Free,Music,Outdoors,Piano
LOCATION:Off Campus Location
CONTACT:
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