Unless otherwise noted, all talks are in 120 Hanes Hall, at 3:30 PM on Mondays and Wednesdays. Prior to the talk, from 3:00-3:30 PM, the audience is invited for refreshments in the lounge on the 3rd floor of Hanes Hall. If you would like to suggest a speaker, or get on our mailing list, please send an email to Dr. Gabor Pataki or Dr. Vladas Pipiras.

In addition to weekly colloquia and seminars, Hotelling lectures are held to honor the memory of Professor Harold Hotelling, first chairman of the “Department of Mathematical Statistics.”

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November 2016

STOR colloquium: Ivo Adan, Eindhoven University of Technology

November 7, 2016 @ 3:30 pm - 4:30 pm

Ivo Adan Technical University of Eindhoven and EURANDOM The Netherlands   A rate balance principle   We introduce a rate balance principle for general (not necessarily Markovian) stochastic processes, with special attention to birth-death like processes. This principle appears to be useful in deriving well-known, as well as new results for various queueing systems.           Refreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall

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STOR colloquium: CANCELLED

November 14, 2016 @ 3:30 pm - 4:30 pm

This colloquium has been cancelled.  We apologize for any inconvenience. STOR colloquium: Vanja Dukic, University of Colorado-Boulder

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STOR colloquium: Stephen Becker, University of Colorado-Boulder

November 21, 2016 @ 3:30 pm - 4:30 pm

Stephen Becker University of Colorado Boulder Efficient robust PCA algorithms for the GPU   We introduce the matrix completion problem and the similar robust PCA (RPCA) problem and discuss their relation to compressed sensing and some of their applications to collaborative filtering, background detection in videos, and neuroscience. We cover some standard algorithms to solve these problems, including proximal gradient descent, Frank-Wolfe/conditional-gradient, and Burer-Monteiro splitting. A natural idea to speed up the algorithms is to run them on the GPU…

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December 2016

STOR colloquium: Elaine McVey, TransLoc/Insightus

December 5, 2016 @ 3:30 pm - 4:30 pm

Title: Commuting, voting, and the off-label use of data   Abstract: The modern practice of data science often involves approaching datasets differently than in traditional statistics.  Two analyses will be presented, both of which use combinations of public datasets in expected and "off-label" ways.  One addresses the need to simulate realistic commuting patterns, and the other evaluates the effects of North Carolina voting site decisions.  In the process of telling the stories of these two data science projects, we'll have…

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January 2017

STOR Colloquium: Santiago Balseiro, Duke University

January 30 @ 3:30 pm - 4:30 pm

Santiago Balseiro Duke University Dynamic Mechanisms with Martingale Utilities We study the dynamic mechanism design problem of a seller who repeatedly sells independent items to a buyer with private values. In this setting, the seller could potentially extract the entire buyer surplus by running efficient auctions and charging an upfront participation fee at the beginning of the horizon. In some markets, such as internet advertising, participation fees are not practical since buyers expect to inspect items before purchasing them. This…

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February 2017

STOR Colloquium: Julie Ivy, North Carolina State University

February 6 @ 3:30 pm - 4:30 pm

Julie Ivy North Carolina State University To be Healthy, Wealthy, and Wise: Using Decision Modeling to Personalize Policy in Health, Hunger Relief, and Education   Decision making to satisfy the basic human needs of health, food, and education is complex, accomplishing this in such a way that solutions are personalized to the needs of the individual has been the focus of my research. This talk will present an overview of my research in the area of decision making under conditions…

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STOR Colloquium: Peter Hoff, Duke University

February 13 @ 3:30 pm - 4:30 pm

Peter Hoff Duke University Adaptive FAB confidence intervals with constant coverage   Abstract: Confidence intervals for the means of multiple normal populations are often based on a hierarchical normal model. While commonly used interval procedures based on such a model have the nominal coverage rate on average across a population of groups, their actual coverage rate for a given group will be above or below the nominal rate, depending on the value of the group mean.   In this talk…

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STOR Colloquium: Gudrun Johnsen, University of Iceland

February 20 @ 3:30 pm - 4:30 pm

Gudrun Johnsen University of Iceland   Title: If you look close enough you can see a whole lot: Data collection and analysis of the Parliamentary Investigation Commission looking into the Icelandic Banking Collapse in 2008   Abstract: The combined collapse of Iceland's three largest banks is the third largest bankruptcy in history and the largest banking system collapse suffered by any country in modern economic history, relative to GDP. In 2008 the Icelandic Parliament installed a Special Investigation Commission (SIC)…

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March 2017

STOR Colloquium: Mariana Olvera-Cravioto, University of California-Berkeley

March 1 @ 3:30 pm - 4:30 pm

Directed complex networks and ranking algorithms In the first part of this talk I will discuss a family of inhomogeneous directed random graphs for modeling complex networks such as the web graph, Twitter, ResearchGate, and other social networks. This class of graphs includes as a special case the classical Erdos-Renyi model, and can be used to replicate almost any type of predetermined degree distributions, in particular, power-law degrees such as those observed in most real-world networks. I will mention during…

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STOR Colloquium: Zhiyi Zhang, UNC Charlotte

March 6 @ 3:30 pm - 4:30 pm

Zhiyi Zhang University of North Carolina at Charlotte Title: Statistical Implications of Turing’s Formula   Abstract: This talk is organized into three parts.   Turing’s formula is introduced. Given an iid sample from a countable alphabet under a probability distribution, Turing’s formula (introduced by Good (1953), hence also known as the Good-Turing formula) is a mind-bending non-parametric estimator of total probability associated with letters of the alphabet that are NOT represented in the sample. Many of its statistical properties were…

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