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UID:427@fds.yale.edu
DTSTART;TZID=America/New_York:20221216T150000
DTEND;TZID=America/New_York:20221216T160000
DTSTAMP:20240226T190411Z
URL:https://fds.yale.edu/events/fds-seminar-aditi-laddha-ga-tech/
SUMMARY:FDS Seminar: Aditi Laddha (GA Tech)
DESCRIPTION:"High-Dimensional Markov Chains and Applications"\n\n\n\nAbstra
ct: A Markov chain is a random process in which the next state is chosen a
ccording to some probability distribution that depends only on the current
state. In a high-dimensional setting\, Markov chains are essential tools
for understanding the geometry of the space and form the backbone of many
efficient randomized algorithms for tasks like optimization\, integration\
, linear programming\, approximate counting\, etc. In this talk\, I will p
rovide an overview of my research on “High-Dimensional Markov Chains\,
” with a focus on the geometric aspects of the chains. I will describe t
wo results that illustrate the importance of Markov chains for designing e
fficient algorithms. First\, I will discuss my work on a barrier-based ran
dom walk for bounding the discrepancy of set systems. I will then present
a general framework for bounding discrepancy in various settings. Second\,
I will describe two Markov chains\, the Weighted Dikin Walk and Coordinat
e Hit-and-Run for sampling convex bodies\, and discuss new techniques for
bounding their convergence rates.\n\n\n\nThis seminar was held virtually o
ver zoom and no recording is available.\n
CATEGORIES:Postdoctoral Applicants,Seminar Series
LOCATION:\, \,
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DTSTART:20221106T010000
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