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VERSION:2.0
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UID:node-10418@prod.cs.cornell.edu
DTSTAMP:20190429T200000Z
DTSTART:20190429T200000Z
DTEND:20190429T210000Z
SUMMARY:Theory Seminar - The Sample Complexity of Toeplitz Covariance Estimation
DESCRIPTION:Cameron Musco, Microsoft Research. Title: The Sample Complexity of Toeplitz Covariance EstimationAbstract:We study the query complexity of estimating the covariance matrix T of a distribution D over d-dimensional vectors, under the assumption that T is Toeplitz. This assumption is standard in a wide variety of signal processing problems, where the covariance between any two measurements only depends on the time or distance between those measurements. In many of these applications, we are interested in estimation strategies that may choose to view only a subset of entries in each d-dimensional sample from D. We care about minimizing both 1) the number of samples taken and 2) the number of entries accessed in each sample, which often equates to minimizing equipment requirements in applications ranging from wireless transmission to advanced imaging....https://prod.cs.cornell.edu/content/theory-seminar-sample-complexity-toeplitz-covariance-estimation
LOCATION:Gates 122 or Bloomberg 497 at NY Tech
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