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UID:597@fds.yale.edu
DTSTART;TZID=America/New_York:20221216T150000
DTEND;TZID=America/New_York:20221216T160000
DTSTAMP:20250916T142119Z
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\nAbstract
 : A Markov chain is a random process in which the next state is chosen acc
 ording to some probability distribution that depends only on the current s
 tate. In a high-dimensional setting\, Markov chains are essential tools fo
 r understanding the geometry of the space and form the backbone of many ef
 ficient randomized algorithms for tasks like optimization\, integration\, 
 linear programming\, approximate counting\, etc. In this talk\, I will pro
 vide an overview of my research on “High-Dimensional Markov Chains\,” 
 with a focus on the geometric aspects of the chains. I will describe two r
 esults that illustrate the importance of Markov chains for designing effic
 ient algorithms. First\, I will discuss my work on a barrier-based random 
 walk for bounding the discrepancy of set systems. I will then present a ge
 neral framework for bounding discrepancy in various settings. Second\, I w
 ill describe two Markov chains\, the Weighted Dikin Walk and Coordinate Hi
 t-and-Run for sampling convex bodies\, and discuss new techniques for boun
 ding their convergence rates.\n\n\n\nThis seminar was held virtually over 
 zoom and no recording is available.\n
CATEGORIES:FDS Events,Postdoctoral Applicants,Seminar Series
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DTSTART:20221106T010000
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