Our upcoming event for the Statistics Department Colloquium Series is scheduled for Monday, October 21 from 12:00 – 1:00pm (ET) and will be an in-person presentation Science Center Rm. 316. Lunch will be provided to guests following the talk. This week's speaker will be Chao Gao of University of Chicago's Statistics department.
Title: Are adaptive robust confidence intervals possible?
Abstract: We study the construction of confidence intervals under Huber’s contamination model. When the contamination proportion is unknown, we characterize the necessary adaptation cost of the problem. In particular, for Gaussian location model, the optimal length of an adaptive confidence interval is proved to be exponentially wider than that of a non-adaptive one. Results for general location models will be discussed. In addition, we also consider the same problem in a network setting for an Erdos-Renyi graph with node contamination. It will be shown that the hardness of the adaptive confidence interval construction is implied by the detection threshold between Erdos-Renyi model and stochastic block model.
LOCATION:Science Center 316 STATUS:CONFIRMED DTSTART:20241021T160000Z DTEND:20241021T170000Z END:VEVENT END:VCALENDAR