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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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