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UID:www.tcs.tifr.res.in/event/1204
DTSTAMP:20230914T125954Z
SUMMARY:Hilbert Schmidt Independence Criterion (HSIC)
DESCRIPTION:Speaker: Jatin Batra\n\nAbstract: \nSuppose we have access to $
 n$ empirical observations of two random variables X\,Y and we want to know
  - are X\,Y independent? One way to answer this is to compute empirical ve
 rsions of various statistical quantities like covariance and mutual inform
 ation. However\, because all we have access to is a finite number ($n$) of
  empirical observations\, we might simply get unlucky. Can we guarantee th
 at our test accuracy increases rapidly with $n$? The Hilbert Schmidt Indep
 endence Criterion (HSIC) proposed by Gretton\, Bousquet\, Smola and Scholk
 opft resolves this issue by providing an estimate of dependence that prova
 bly gets more accurate at a $1/\\sqrt{n}$ rate. In this talk\, I will desc
 ribe (following Gretton et al. in http://www.gatsby.ucl.ac.uk/~gretton/pap
 ers/GreBouSmoSch05.pdf) how HSIC arises quite naturally as a kernel invari
 ant version of the covariance estimate and also allude to some later appli
 cations of HSIC.\n
URL:https://www.tcs.tifr.res.in/web/events/1204
DTSTART;TZID=Asia/Kolkata:20220513T160000
DTEND;TZID=Asia/Kolkata:20220513T170000
LOCATION:A-201 (STCS Seminar Room)
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