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UID:68@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20240812T143000
DTEND;TZID=Asia/Kolkata:20240812T153000
DTSTAMP:20240730T054550Z
URL:https://cds.iisc.ac.in/events/seminar-cds-102-0230-august-a-new-locall
 y-adaptive-nonparametric-regression-method/
SUMMARY:{Seminar} @ CDS: #102: 02:30 August: "A New Locally Adaptive Nonpar
 ametric Regression Method."
DESCRIPTION:Department of Computational and Data Sciences\nDepartment Semin
 ar\n\n\n\nSpeaker : Prof. Sabyasachi Chatterjee\, University of Illinois a
 t Urbana Champaign.\nTitle : A New Locally Adaptive Nonparametric Regressi
 on Method.\nDate &amp\; Time : August 12\, 2024\, 2:30 PM\nVenue : # 102\,
  CDS Seminar Hall\n\n\n\nABSTRACT\n\nWe propose and study a new locally ad
 aptive nonparametric regression method. The method performs variable bandw
 idth local averaging/local polynomial regression. To certify its local ada
 ptivity we show that it adapts near optimally to the local Holder smoothne
 ss exponent of the regression function at any point in the domain. Despite
  the vast literature on Nonparametric Regression\, we only know one existi
 ng method which attains such local adaptivity proveably. This method is kn
 own as Lepski's method. There are some drawbacks to Lepski's method such a
 s a) it is specifically tailored to a given class of functions such as Hol
 der Smooth function class b) it is rather theoretical and impractical to i
 mplement with effectively many tuning parameters. Our proposed method seem
 s to overcome these drawbacks. Firstly\, our method is defined without any
  reference to any function class and secondly there is only one tuning par
 ameter\, which when set properly\, adjusts all the bandwidths at all locat
 ions near optimally. Our method is practically implementable and appears t
 o perform reasonably well in our numerical experiments.\n\nBIO: Dr. Sabyas
 achi Chatterjee is currently working as an Associate Professor in the Depa
 rtment of Statistics at the University of Illinois at Urbana Champaign. He
  earned his PhD in Statistics at Yale University\, USA. Then\, he worked a
 s a Postdoctoral Research Scholar and William Kruskal Instructor in the De
 partment of Statistics at the University of Chicago\, USA. His research in
 terests lie in Mathematical Statistics and Machine Learning Theory\, along
  with their connections with Information Theory\, Probability\, and Optimi
 zation. For more about his research\, please see https://sabyasachi.web.il
 linois.edu/\n\nHost Faculty: Dr. Ratikanta Behera\n\n\n\nALL ARE WELCOME
CATEGORIES:Events,Talks
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