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X-WR-CALNAME:Department of Statistics and Operations Research
X-ORIGINAL-URL:https://stat-or.unc.edu
X-WR-CALDESC:Events for Department of Statistics and Operations Research
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DTSTART:20160313T070000
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DTSTART:20161106T060000
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DTSTART:20170312T070000
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160912T153000
DTEND;TZID=America/New_York:20160912T163000
DTSTAMP:20210515T194827
CREATED:20160902T190454Z
LAST-MODIFIED:20170215T212350Z
UID:1860-1473694200-1473697800@stat-or.unc.edu
SUMMARY:STOR Colloquium: Alfredo Garcia\, ARO and University of Florida
DESCRIPTION:Alfredo Garcia\, Army Research Office (ARO) and University of Florida \n \nIterative Mechanisms for Electricity Markets \n \nAbstract: We consider the problem of designing the rules by which dispatch and payment to electricity market participants are gradually adjusted while taking into account network and reliability constraints so as to ensure the market clears with an efficient outcome. Small adjustments (which require minimal information from market participants at each iteration) facilitate the identification of incentives for ensuring truthful reporting of private information. We propose a class of iterative mechanisms and show this class exhibits many desirable properties: incentive compatibility\, efficiency\, individual rationality and (weak) budget balance. We also analyze an iterative mechanism for stochastic market clearing\, a pressing need given the increasing penetration of highly intermittent renewable generation technologies. In this case\, the marginal cost of adjustments may only be estimated with some error. We show that truthful reporting is a Nash equilibrium and the resulting dispatch converges almost surely to the efficient dispatch. \nBased on the paper posted on the Arxiv: http://arxiv.org/abs/1608.08987 \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20160919T153000
DTEND;TZID=America/New_York:20160919T163000
DTSTAMP:20210515T194827
CREATED:20160902T190558Z
LAST-MODIFIED:20170215T212350Z
UID:1862-1474299000-1474302600@stat-or.unc.edu
SUMMARY:STOR Colloquium: Bin Hu\, University of North Carolina at Chapel Hill
DESCRIPTION:Bin Hu \nUniversity of North Carolina at Chapel Hill\, Kenan-Flagler Business School\n \n\n\nIs Reshoring Better than Offshoring? The Effect of Offshore \nSupply Dependence\n \nIn this paper we investigate the effect of offshore supply dependence (OSD) on offshoring-reshoring profit comparisons. We find that OSD hampers a reshoring manufacturer’s responsiveness to demand information updates and may significantly affect offshoring-reshoring comparisons\, such that reshoring may yield lower profits than offshoring in many cases\, including when offshoring has no baseline-cost advantage. We then show that OSD also affects how salient costs such as customs duties and shipping costs influence offshoring-reshoring profit comparisons. We further identify common-component designs as a mitigating measure to make reshoring more appealing under OSD\, and numerically confirm the robustness of our results. \n \nhttp://papers.ssrn.com/sol3/papers.cfm?abstract_id=2645328 \n\n \n \n Refreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-2/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161003T153000
DTEND;TZID=America/New_York:20161003T163000
DTSTAMP:20210515T194827
CREATED:20160906T144800Z
LAST-MODIFIED:20170215T212350Z
UID:1880-1475508600-1475512200@stat-or.unc.edu
SUMMARY:STOR colloquium: Nelson Antunes\, CEMAT/University of Lisbon
DESCRIPTION:Nelson Antunes\nCEMAT/University of Lisbon and University of Algarve \n \nSampling Internet traffic: estimation of flow distributions\nIn this talk\, the focus is on recovering the flow (sequence of packets sharing common attributes) size and duration distributions from sampled Internet traffic using a number of previously introduced packet sampling algorithms. Assuming a basic probabilistic flow model\, the distribution of flow durations is expressed in terms of the distributions of flow sizes and flow IATs (interarrival times between packets). The available estimation methods of the flow size distribution through inversion are then discussed. Inverse equations that allow recovering the distribution of flow IATs from sampled flows and hence the flow duration distribution are presented. An asymptotic approach is also considered to estimate directly the distribution tails of flow durations and sizes from the sampled flow quantities. Both the inversion and asymptotic approaches are evaluated on two Internet traces\, along with a discussion on combining the inversion and asymptotic approaches for a more accurate estimation of both the main body and the tail of the flow distributions. \n \n(This is a joint work with Vladas Pipiras at UNC-Chapel Hill.) \n\n \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-nelson-antunes-cematuniversity-of-lisbon/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161010T153000
DTEND;TZID=America/New_York:20161010T163000
DTSTAMP:20210515T194827
CREATED:20160906T144918Z
LAST-MODIFIED:20170215T212350Z
UID:1882-1476113400-1476117000@stat-or.unc.edu
SUMMARY:STOR colloquium: Joe Guinness\, North Carolina State University
DESCRIPTION:Joe Guinness \nNorth Carolina State University \n \nPermutation methods for sharpening Gaussian process approximations \n \nVecchia’s approximate likelihood for Gaussian process parameters depends on how the observations are ordered\, which can be viewed as a deficiency because the exact likelihood is permutation-invariant. I take the alternative standpoint that the ordering of the observations is an aspect that can be tuned to sharpen the approximations. I show that advantageously chosen orderings of the observations can drastically improve the approximations. In addition to the permutation results\, automatic methods for grouping calculations of components of the approximation are introduced\, having the result of simultaneously improving the quality of the approximation and reducing its computational burden. In one common setting\, reordering combined with grouping reduces the Kullback-Leibler divergence from the target model by a factor of 80 and the computation time by a factor of 2 compared to ungrouped approximations with a default ordering. The claims are supported by theory and numerical results\, and details of implementation are provided\, including how to efficiently find the orderings and ordered nearest neighbors\, and how to use the approximations for prediction and conditional simulation. An application to uncertainty quantification in interpolations of space-time satellite data is presented. \n \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall \n
URL:https://stat-or.unc.edu/event/stor-colloquium-joe-guinness-north-carolina-state-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161017T153000
DTEND;TZID=America/New_York:20161017T163000
DTSTAMP:20210515T194827
CREATED:20160906T145045Z
LAST-MODIFIED:20170215T212349Z
UID:1884-1476718200-1476721800@stat-or.unc.edu
SUMMARY:STOR colloquium: Dirk Lorenz\, Braunschweig Technical University
DESCRIPTION:Dirk Lorenz \nBraunschweig Technical University \n \nProbabilistic Image Models and Extensions of the\nPerona-Malik Filter \nThe Perona-Malik model has been very successful at restoring images from noisy input. In this paper\, we show how the Perona-Malik model can be reinterpreted and extended using the language of Gaussian scale mixtures. Specifically\, we show how the expectation-maximization EM algorithm applied to Gaussian scale mixtures leads to the lagged-diffusivity algorithm for computing stationary points of the Perona-Malik diffusion equations. Moreover\, we show how mean field approximations to these Gaussian scale mixtures lead to a modification of the lagged-diffusivity algorithm that better captures the uncertainties in the restoration. Since this modification can be hard to compute in practice we propose relaxations to the mean field objective to make the algorithm computationally feasible. Our numerical experiments show that this modified lagged-diffusivity algorithm often performs better at restoring textured areas and fuzzy edges than the unmodified algorithm. As a second application of the Gaussian scale mixture framework\, we show how an efficient sampling procedure can be obtained for the probabilistic model\, making the computation of the conditional mean and other expectations algorithmically feasible. Again\, the resulting algorithm has a strong resemblance to the lagged-diffusivity algorithm. \n \n \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-dirk-lorenz-braunschweig-technical-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161031T153000
DTEND;TZID=America/New_York:20161031T163000
DTSTAMP:20210515T194827
CREATED:20160906T145152Z
LAST-MODIFIED:20170215T212349Z
UID:1886-1477927800-1477931400@stat-or.unc.edu
SUMMARY:STOR colloquium: Seyed Emadi\, University of North Carolina at Chapel Hill
DESCRIPTION:Impact of Delay Announcements in Call Centers: \nAn Empirical Approach \n \nWe undertake an empirical study of the impact of delay announcements on callers’ abandonment behavior and the performance of a call center with two priority classes. A Cox regression analysis reveals that in this call center\, callers’ abandonment behavior is affected by the announcement messages heard. To account for this\, we formulate a structural estimation model of callers’ (endogenous) abandonment decisions. In this model\, callers are forward-looking utility maximizers and make their abandonment decisions by solving an optimal stopping problem. Each caller receives a reward from service and incurs a linear cost of waiting. The reward and per-period waiting cost constitute the structural parameters that we estimate from the data of callers’ abandonment decisions as well as the announcement messages heard. The call center performance is modeled by a Markovian approximation. The main methodological contribution is the definition of an equilibrium in steady state as one where callers’ expectation of their waiting time\, which affects their (rational) abandonment behavior\, matches their actual waiting time in the call center\, and its characterization as the solution of a set of non-linear equations. A counterfactual analysis shows that callers react to longer delay announcements by abandoning earlier\, that less patient callers as characterized by their reward and cost parameters react more to delay announcements\, and that congestion in the call center at the time of the call affects caller reactions to delay announcements. \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall \n
URL:https://stat-or.unc.edu/event/stor-colloquium-seyed-emadi-university-of-north-carolina-at-chapel-hill/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161107T143000
DTEND;TZID=America/New_York:20161107T153000
DTSTAMP:20210515T194827
CREATED:20160906T145250Z
LAST-MODIFIED:20170215T212349Z
UID:1888-1478529000-1478532600@stat-or.unc.edu
SUMMARY:STOR colloquium: Ivo Adan\, Eindhoven University of Technology
DESCRIPTION:Ivo Adan \nTechnical University of Eindhoven and\nEURANDOM The Netherlands \n \nA rate balance principle \n \nWe 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. \n \n \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-ivo-adan-eindhoven-university-of-technology/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161114T143000
DTEND;TZID=America/New_York:20161114T153000
DTSTAMP:20210515T194827
CREATED:20160906T145348Z
LAST-MODIFIED:20170215T212348Z
UID:1890-1479133800-1479137400@stat-or.unc.edu
SUMMARY:STOR colloquium: CANCELLED
DESCRIPTION:This colloquium has been cancelled. We apologize for any inconvenience. \nSTOR colloquium: Vanja Dukic\, University of Colorado-Boulder
URL:https://stat-or.unc.edu/event/stor-colloquium-vanja-dukic-university-of-colorado-boulder/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161121T143000
DTEND;TZID=America/New_York:20161121T153000
DTSTAMP:20210515T194827
CREATED:20160906T145438Z
LAST-MODIFIED:20170215T212348Z
UID:1892-1479738600-1479742200@stat-or.unc.edu
SUMMARY:STOR colloquium: Stephen Becker\, University of Colorado-Boulder
DESCRIPTION:Stephen Becker \nUniversity of Colorado Boulder \n\nEfficient robust PCA algorithms for the GPU \n \nWe 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 to take advantage of the many parallel threads of a GPU. This works well for some matrix completion algorithms\, but the RPCA algorithms do not parallelize well. This motivates our new algorithm for RPCA which is designed to run well on the GPU\, and we show results with major improvements over existing algorithms. \n \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-stephen-becker-university-of-colorado-boulder/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20161205T143000
DTEND;TZID=America/New_York:20161205T153000
DTSTAMP:20210515T194827
CREATED:20160906T145531Z
LAST-MODIFIED:20170215T212348Z
UID:1894-1480948200-1480951800@stat-or.unc.edu
SUMMARY:STOR colloquium: Elaine McVey\, TransLoc/Insightus
DESCRIPTION:Title: Commuting\, voting\, and the off-label use of data \n \nAbstract: 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 an opportunity to reflect on the nature of data science. \n \nRefreshments will be served in the lounge at 3:30pm
URL:https://stat-or.unc.edu/event/stor-colloquium-elaine-mcvey-translocinsightus/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170130T143000
DTEND;TZID=America/New_York:20170130T153000
DTSTAMP:20210515T194827
CREATED:20170117T155930Z
LAST-MODIFIED:20170215T220855Z
UID:2574-1485786600-1485790200@stat-or.unc.edu
SUMMARY:STOR Colloquium: Santiago Balseiro\, Duke University
DESCRIPTION:Santiago Balseiro \nDuke University \nDynamic Mechanisms with Martingale Utilities \nWe 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 motivates us to study the design of dynamic mechanisms under successively more stringent requirements that capture the implicit business constraints of these markets. We first consider a “periodic individual rationality constraint\,” which limits the mechanism to charge at most the buyer’s value in each period. While this prevents large upfront participation fees\, the seller can still design mechanisms that spread a participation fee across the first few auctions. These mechanisms have the unappealing feature that they provide close-to-zero buyer utility in the first auctions in exchange for higher utility in future auctions. To address this problem\, we introduce a “martingale utility constraint\,” which imposes the requirement that from the perspective of the buyer\, the next item’s expected utility is equal to the present one’s. Our main result is providing a dynamic auction satisfying martingale utility and periodic individual rationality whose profit loss with respect to first-best (full extraction of buyer surplus) is optimal up to polylogarithmic factors. The proposed mechanism is a dynamic two-tier auction with a hard floor and a soft floor that allocates the item whenever the buyer’s bid is above the hard floor and charges the minimum of the bid and the soft floor. \nJoint work the Vahab Mirrokni (Google Research) and Renato Paes Leme (Google Research). \n \nThe paper is available at https://ssrn.com/abstract=2821261 \n\nSantiago Balseiro’s web page \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall \n
URL:https://stat-or.unc.edu/event/stor-colloquium-santiago-balseiro-duke-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170206T143000
DTEND;TZID=America/New_York:20170206T153000
DTSTAMP:20210515T194827
CREATED:20170117T160109Z
LAST-MODIFIED:20170215T220855Z
UID:2576-1486391400-1486395000@stat-or.unc.edu
SUMMARY:STOR Colloquium: Julie Ivy\, North Carolina State University
DESCRIPTION:Julie Ivy \nNorth Carolina State University \nTo be Healthy\, Wealthy\, and Wise: Using Decision Modeling to \nPersonalize Policy in Health\, Hunger Relief\, and Education \n \nDecision 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 of uncertainty with a focus on human-centric decision problems in three primary areas: health care\, humanitarian logistics\, and education. This research seeks to inform decision making with the goal of improving decision quality. To this end\, this research utilizes and develops theory in the areas of Markov decision processes (MDPs)\, semi-Markov decision processes (SMDPs)\, partially observable Markov decision processes (POMDPs)\, simulation\, and Bayesian decision analysis to address these real world problems. This research has made an impact on how researchers and practitioners address complex societal issues\, such as health disparities\, public health preparedness\, hunger relief\, student performance\, and personalized medical decision-making and has been funded by AHRQ\, CDC\, NSF\, Clinton Health Access Initiative\, and the UNC Cancer Center. \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-julie-ivy-north-carolina-state-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170213T143000
DTEND;TZID=America/New_York:20170213T153000
DTSTAMP:20210515T194827
CREATED:20170117T160202Z
LAST-MODIFIED:20170215T220854Z
UID:2578-1486996200-1486999800@stat-or.unc.edu
SUMMARY:STOR Colloquium: Peter Hoff\, Duke University
DESCRIPTION:Peter Hoff \nDuke University \nAdaptive FAB confidence intervals with constant coverage \n \nAbstract: 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. \n \nIn this talk I present confidence interval procedures that have constant frequentist coverage rates and that make use of information about across-group heterogeneity\, resulting in constant-coverage intervals that are narrower than standard t-intervals on average across groups. These intervals are obtained by inverting Bayes-optimal frequentist tests\, and so are “frequentist\, assisted by Bayes” (FAB). I present some asymptotic optimality results and some extensions to other multiparameter models\, such as linear regression. \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-peter-hoff-duke-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170220T143000
DTEND;TZID=America/New_York:20170220T153000
DTSTAMP:20210515T194827
CREATED:20170117T160252Z
LAST-MODIFIED:20170215T220854Z
UID:2580-1487601000-1487604600@stat-or.unc.edu
SUMMARY:STOR Colloquium: Gudrun Johnsen\, University of Iceland
DESCRIPTION:Gudrun Johnsen \nUniversity of Iceland \n \nTitle: 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 \n \nAbstract: 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) with exceptional data privileges to respond to the outcry of the Icelandic public and its demand to know why the banks failed. The SIC data collection\, data analysis and 2400-page report match few others in the public domain\, as Commissioners could cease all data considered necessary for the Investigation.
URL:https://stat-or.unc.edu/event/stor-colloquium-gundrun-johnson-university-of-iceland/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170301T143000
DTEND;TZID=America/New_York:20170301T153000
DTSTAMP:20210515T194827
CREATED:20170216T140137Z
LAST-MODIFIED:20170216T140137Z
UID:2767-1488378600-1488382200@stat-or.unc.edu
SUMMARY:STOR Colloquium: Mariana Olvera-Cravioto\, University of California-Berkeley
DESCRIPTION:Directed complex networks and ranking algorithms \nIn 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 the talk the main properties of this family of random graphs and explain how its parameters can be used to represent important data attributes that influence the connectivity of nodes in the network. \nIn the second part of the talk I will explain how ranking algorithms such as Google’s PageRank can be used to identify highly influential nodes in a network\, and present some recent results describing the distribution of the ranks computed by such algorithms. This work extends prior work done for the directed configuration model to the new class of inhomogeneous directed random graphs mentioned above\, and provides a more natural way to model the relationship between highly ranked nodes and their attributes. If time allows\, I will mention some interesting stochastic simulation challenges related to this problem. \n \nRefreshments will be served in the lounge area of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-mariana-olvera-cravioto-university-of-california-berkeley/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170306T143000
DTEND;TZID=America/New_York:20170306T153000
DTSTAMP:20210515T194827
CREATED:20170117T160343Z
LAST-MODIFIED:20170221T172152Z
UID:2582-1488810600-1488814200@stat-or.unc.edu
SUMMARY:STOR Colloquium: Zhiyi Zhang\, UNC Charlotte
DESCRIPTION:Zhiyi Zhang \nUniversity of North Carolina at Charlotte \nTitle: Statistical Implications of Turing’s Formula \n \nAbstract: This talk is organized into three parts. \n \n\nTuring’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 not clearly known for a stretch of nearly sixty years until recently. Some of the newly established results\, including various asymptotic normal laws\, are described.\n\n \n\nTuring’s perspective is described. Turing’s formula brought about a new perspective (or a new characterization) of probability distributions on general countable alphabets. The new perspective in turn provides a new way to do statistics on alphabets\, where the usual statistical concepts associated with random variables (on the real line) no longer exist\, for example\, moments\, tails\, coefficients of correlation\, characteristic functions don’t exist on alphabets (a major challenge of modern data sciences). The new perspective\, in the form of entropic basis\, is introduced.\n\n \n\nSeveral applications are presented\, including estimation of information entropy and diversity indices.
URL:https://stat-or.unc.edu/event/stor-colloquium-zhiyi-zhang-unc-charlotte/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170403T153000
DTEND;TZID=America/New_York:20170403T163000
DTSTAMP:20210515T194827
CREATED:20170117T160432Z
LAST-MODIFIED:20170328T132756Z
UID:2584-1491233400-1491237000@stat-or.unc.edu
SUMMARY:STOR Colloquium: Hongtu Zhu\, MD Anderson
DESCRIPTION:Hongtu Zhu \nUniversity of North Carolina at Chapel Hill\, and The University of Texas MD Anderson Cancer Center \n \nTitle: Statistical Challenges\, Opportunities\, and Strategies in Large-Scale Medical Studies \nWith the rapid growth of modern technology\, many biomedical studies have collected data across different sources (e.g.\, imaging\, genetics\, and clinical) in an unprecedented scale. The integration of such ultra high-dimensional data raises many statistical challenges\, rendering most existing statistical methods and old data platform no longer suitable and thus underscoring the great need for methodological developments from a rigorous perspective. To address these challenges\, I will highlight several key statistical opportunities and strategies in big data integration and analysis through several interrelated projects. \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-hongtu-zhu-md-anderson/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170410T153000
DTEND;TZID=America/New_York:20170410T163000
DTSTAMP:20210515T194827
CREATED:20170117T160518Z
LAST-MODIFIED:20170410T131755Z
UID:2586-1491838200-1491841800@stat-or.unc.edu
SUMMARY:CANCELLED STOR Colloquium
DESCRIPTION:Philip Ernst \nRice University \n \nTitle: Yule’s “Nonsense Correlation” Solved! \n \nAbstract: In this talk\, I will discuss how I recently resolved a longstanding open statistical problem. The problem\, formulated by the British statistician Udny Yule in 1926\, is to mathematically prove Yule’s 1926 empirical finding of “nonsense correlation.” We solve the problem by analytically determining the second moment of the empirical correlation coefficient of two independent Wiener processes. Using tools from Fredholm integral equation theory\, we calculate the second moment of the empirical correlation to obtain a value for the standard deviation of the empirical correlation of nearly .5. The “nonsense” correlation\, which we call “volatile” correlation\, is volatile in the sense that its distribution is heavily dispersed and is frequently large in absolute value. It is induced because each Wiener process is “self-correlated” in time. This is because a Wiener process is an integral of pure noise and thus its values at different time points are correlated. In addition to providing an explicit formula for the second moment of the empirical correlation\, we offer implicit formulas for higher moments of the empirical correlation. The full paper is currently in press at The Annals of Statistics and can be found at http://www.imstat.org/aos/AOS1509.pdf.
URL:https://stat-or.unc.edu/event/stor-colloquium-philip-ernst-rice-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170417T153000
DTEND;TZID=America/New_York:20170417T163000
DTSTAMP:20210515T194827
CREATED:20170117T160611Z
LAST-MODIFIED:20170410T202935Z
UID:2588-1492443000-1492446600@stat-or.unc.edu
SUMMARY:STOR Colloquium: Ilse Ipsen\, North Carolina State University
DESCRIPTION:Ilse Ipsen \nNorth Carolina State University\n \nRandomized Algorithms for Matrix Computations \n \nThe emergence of massive data sets\, over the past fifteen or so years\, has led to the development of Randomized Numerical Linear Algebra. Fast and accurate randomized matrix algorithms are being designed for applications like machine learning\, population genomics\, astronomy\, nuclear engineering\, and optimal experimental design. \nWe give a flavour of randomized algorithms for the solution of least squares/regression problems and\, if time permits\, for the computation of logdeterminants. Along the way we illustrate important concepts from numerical analysis (conditioning and pre-conditioning) and statistics (sampling and leverage scores).
URL:https://stat-or.unc.edu/event/stor-colloquium-ilse-ipsen-north-carolina-state-university/
LOCATION:Hanes Hall
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170503T153000
DTEND;TZID=America/New_York:20170503T163000
DTSTAMP:20210515T194827
CREATED:20170406T144008Z
LAST-MODIFIED:20170406T144008Z
UID:2891-1493825400-1493829000@stat-or.unc.edu
SUMMARY:STOR Colloquium: Jong-Shi Pang\, U. of Southern California
DESCRIPTION:Jong-Shi Pang \nUniversity of Southern California \nTitle: Structural Properties of Affine Sparsity Constraints \n \nAbstract: We introduce a new constraint system for sparse variable selection in statistical learning. Such a \nsystem arises when there are logical conditions on the sparsity of certain unknown model parameters that need \nto be incorporated into their selection process. Formally\, extending a cardinality constraint\, an affine sparsity \nconstraint (ASC) is defined by a linear inequality with two sets of variables: one set of continuous variables \nand the other set represented by their nonzero patterns. This paper studies an ASC system consisting \nof finitely many affine sparsity constraints. We investigate a number of fundamental structural properties \nof the solution set of such a non-standard system of inequalities\, including its closedness and the description \nof its closure\, continuous approximations and their set convergence\, and characterizations of its tangent \ncones for use in optimization. Based on the obtained structural properties of an ASC system\, we establish \nthe convergence of B(ouligand) stationary solutions when the ASC is approximated by surrogates of the \nell0 step function commonly employed in sparsity representation. Our study lays a solid mathematical \nfoundation for solving optimization problems involving these affine sparsity constraints through their \ncontinuous approximations. \n \nThis is joint work with Professor Hongbo Dong (Washington State University) and graduate student \nMiju Ahn (University of Southern California). \n \nRefreshments will be served in the lounge area of Hanes Hall at 3:00 pm
URL:https://stat-or.unc.edu/event/stor-colloquium-jong-shi-pang-u-of-southern-california/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170828T153000
DTEND;TZID=America/New_York:20170828T163000
DTSTAMP:20210515T194827
CREATED:20170811T203540Z
LAST-MODIFIED:20170822T182947Z
UID:3086-1503934200-1503937800@stat-or.unc.edu
SUMMARY:STOR Colloquium: Ion Necoara\, Polytechnic University of Bucharest
DESCRIPTION:Ion Necoara \nPolytechnic University of Bucharest \n \nConditions for linear convergence of (stochastic) first order methods \n \nFor convex optimization problems deterministic first order methods have linear convergence when the objective function is smooth and strongly convex. Moreover\, under the same conditions – smoothness and strong convexity – sublinear convergence rates have been derived for stochastic first order methods. However\, in many applications (machine learning\, statistics\, control\, signal processing) the strong convexity condition does not hold\, but the objective function still has a special structure. In this talk we replace the smoothness/strong convexity conditions with several other conditions\, that are less conservative\, for which we are able to prove that several (stochastic) first order methods are converging linearly. We also provide necessary conditions for linear convergence of (stochastic) gradient method. Finally\, we discuss several applications of these results (Lasso problem\, linear systems\, linear programming\, convex feasibility\, etc). \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall \n
URL:https://stat-or.unc.edu/event/stor-colloquium-ion-necoara/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170906T153000
DTEND;TZID=America/New_York:20170906T163000
DTSTAMP:20210515T194827
CREATED:20170829T135641Z
LAST-MODIFIED:20170831T193636Z
UID:3122-1504711800-1504715400@stat-or.unc.edu
SUMMARY:STOR Colloquium: Hao Chen\, UC Davis
DESCRIPTION:Change-point detection for locally dependent data \n \nLocal dependence is common in multivariate and non-Euclidean data sequences\, such as network data. We consider the testing and estimation of change-points in such sequences. A new way of permutation\, circular block permutation with a randomized starting point\, is proposed and studied for a scan statistic utilizing graphs representing the similarity between observations. The proposed permutation approach could correctly address for local dependence and make it possible the theoretical treatments for the non-parametric graph-based scan statistic for locally dependent data. We derive accurate analytic approximations to the significance of graph-based scan statistics under the circular block permutation framework\, facilitating its application to locally dependent multivariate or object data sequences. \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-hao-chen-uc-davis/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170911T153000
DTEND;TZID=America/New_York:20170911T163000
DTSTAMP:20210515T194827
CREATED:20170829T135845Z
LAST-MODIFIED:20170911T191934Z
UID:3124-1505143800-1505147400@stat-or.unc.edu
SUMMARY:STOR Colloquium: Iain Carmichael\, UNC-Chapel Hill
DESCRIPTION:Title: Data science and the undergraduate curriculum \n \nLast semester we developed and taught a new course titled “Introduction to Data Science” for the undergraduate analytics major at UNC (see https://idc9.github.io/stor390/). The core topics of the class were: programming in R (working with data\, visualization\, functions/loops/conditionals)\, data analysis (exploratory\, predictive and inferential)\, acquiring data (APIs\, web scraping)\, communication (e.g. literate programming\, effective visualization)\, and some additional topics (text data and data ethics/inequality). This course differed from existing courses in a number of ways including: more code than math\, focus on real data/questions\, a final project\, and open source course material. We present the overall goals of the class\, the teaching methods\, design choices and our own takeaways from the class. Drawing on our own experiences and a survey of the literature on advancing the undergraduate statistics curriculum we discuss future directions for both this course and the rest of the curriculum. \nLink to presentation slides: \nhttps://docs.google.com/presentation/d/1XUaNIybiPD6OpTs-ou5baSUQYiUOJuafXQsvEwrChjc/edit?usp=sharing \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-iain-davis-unc-chapel-hill/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20170918T153000
DTEND;TZID=America/New_York:20170918T163000
DTSTAMP:20210515T194827
CREATED:20170829T165631Z
LAST-MODIFIED:20170908T200142Z
UID:3126-1505748600-1505752200@stat-or.unc.edu
SUMMARY:STOR Colloquium: Philip Ernst\, Rice
DESCRIPTION:Yule’s “Nonsense Correlation” Solved! \n \nIn this talk\, I will discuss how I recently resolved a longstanding open statistical problem. The problem\, formulated by the British statistician Udny Yule in 1926\, is to mathematically prove Yule’s 1926 empirical finding of “nonsense correlation.” We solve the problem by analytically determining the second moment of the empirical correlation coefficient of two independent Wiener processes. Using tools from Fredholm integral equation theory\, we calculate the second moment of the empirical correlation to obtain a value for the standard deviation of the empirical correlation of nearly .5. The “nonsense” correlation\, which we call “volatile” correlation\, is volatile in the sense that its distribution is heavily dispersed and is frequently large in absolute value. It is induced because each Wiener process is “self-correlated” in time. This is because a Wiener process is an integral of pure noise and thus its values at different time points are correlated. In addition to providing an explicit formula for the second moment of the empirical correlation\, we offer implicit formulas for higher moments of the empirical correlation. The full paper is currently in press at The Annals of Statistics and can be found at https://projecteuclid.org/euclid.aos/1498636874. \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-philip-ernst-rice/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20171002T153000
DTEND;TZID=America/New_York:20171002T163000
DTSTAMP:20210515T194827
CREATED:20170811T203647Z
LAST-MODIFIED:20170905T165354Z
UID:3088-1506958200-1506961800@stat-or.unc.edu
SUMMARY:STOR Colloquium: Sercan Yildiz\, SAMSI
DESCRIPTION:Title: Polynomial Optimization with Sums-of-Squares Interpolants\nAbstract: Sums-of-squares certificates define a hierarchy of relaxations for polynomial optimization problems which are parameterized with the degree of the polynomials in the sums-of-squares representation. Each level of the hierarchy generates a lower bound on the true optimal value\, which can be computed in polynomial time via semidefinite programming\, and these lower bounds converge to the true optimal value under mild assumptions. However\, solving the semidefinite programs that arise from sums-of-squares relaxations poses practical challenges at higher levels of the hierarchy. First\, the sizes of these semidefinite programs depend quadratically on the number of monomials in the sums-of-squares representations. Second\, numerical problems are often encountered. In this talk\, we show that non-symmetric conic programming and polynomial interpolation techniques can be used to optimize efficiently over the sums-of-squares cone. Preliminary computational results indicate that our method compares favorably against standard approaches. The talk is based on joint work with David Papp.
URL:https://stat-or.unc.edu/event/stor-colloquium-sercan-yildiz/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20171009T153000
DTEND;TZID=America/New_York:20171009T163000
DTSTAMP:20210515T194827
CREATED:20170811T203752Z
LAST-MODIFIED:20170926T171305Z
UID:3090-1507563000-1507566600@stat-or.unc.edu
SUMMARY:STOR Colloquium: Patrick Wolfe\, Purdue University
DESCRIPTION:Title: Nonparametric network comparison\n \nUnderstanding how two networks differ\, or quantifying the degree to which a single network departs from a given model\, is a challenging question in modern mathematical statistics. Here we show how subgraph densities\, which for large graphs play a role analogous to moments in the context of random variables\, enable a natural means of nonparametric network comparison. Coupled with a partial order derived from a notion of subgraph scale\, we then show how this leads to an automated\, computationally scalable comparison algorithm with provable properties. \nJoint work with P.-A. Maugis and S. C. Olhede; preprint at https://arxiv.org/abs/1705.05677. \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-patrick-wolfe-purdue/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20171016T153000
DTEND;TZID=America/New_York:20171016T163000
DTSTAMP:20210515T194827
CREATED:20170811T204013Z
LAST-MODIFIED:20171009T183335Z
UID:3093-1508167800-1508171400@stat-or.unc.edu
SUMMARY:STOR Colloquium: Srinagesh Gavirneni\, Cornell
DESCRIPTION:Title: Co-opetition in Service Clusters with Waiting-Area Entertainment \n Link to paper: Co-opetition-Service-Clusters\n \nAbstract: Unoccupied waiting feels longer than it actually is. Service providers operationalize this psychological principle by offering entertainment options in waiting areas. In a service cluster with a shared waiting space\, firms have an opportunity to cooperate in the investment for providing entertainment options while competing on other service dimensions. In this paper\, we develop a parsimonious model of co-opetition in a service cluster with shared entertainment options for waiting customers (e.g.\, a boardwalk). By comparing the case of co-opetition with two benchmarks (monopoly\, and duopoly competition)\, we demonstrate that a service provider\, which would otherwise be a local monopolist\, can achieve a higher pro fit by joining a service cluster and engaging in co-opetition: we numerically show that the average firm profit under co-opetition is 7.65% higher than under monopoly. Achieving such benefits\, however\, requires a cost-allocation scheme properly addressing a fairness-efficiency tradeoff. A pursuit of fairness may backfire and lead to even lower profits than under pure competition. We show that as much as co-opetition facilitates resource sharing in a service cluster\, it also heightens price competition. Furthermore\, as the intensity of price competition increases\, surprisingly\, service providers may opt to charge higher service fees\, albeit while providing a higher entertainment level. \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall \nNagesh Gavirneni is a professor of operations management in the Samuel Curtis Johnson Graduate School of Management at Cornell University. His research interests are in the areas of supply chain management\, inventory control\, production scheduling\, simulation and optimization. He is now using these models and methodologies to solve problems in healthcare\, agriculture and humanitarian logistics in developing countries. Previously\, he was an assistant professor in the Kelley School of Business at Indiana University\, the chief algorithm design engineer of SmartOps\, a Software Architect at Maxager Technology\, Inc. and a research scientist with Schlumberger. He has an undergraduate degree in Mechanical Engineering from IIT-Madras\, a Master’s degree from Iowa State University\, and a Ph.D. from Carnegie Mellon University. \n
URL:https://stat-or.unc.edu/event/stor-colloquium-srinagesh-gavirneni-cornell/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20171023T153000
DTEND;TZID=America/New_York:20171023T163000
DTSTAMP:20210515T194827
CREATED:20170811T204130Z
LAST-MODIFIED:20171004T173406Z
UID:3095-1508772600-1508776200@stat-or.unc.edu
SUMMARY:STOR Colloquium: Jonathan Taylor\, Stanford
DESCRIPTION:Selective sampling after solving a convex problem \n \nRecent work in the conditional approach to selective inference requires describing potentially complex conditional distributions. In this work\, we describe a model-agnostic simplification to such conditional distributions when the selection stage can be expressed as a sequence of (randomized) convex programs with convex loss and structure inducing constraints or penalties. Our main result is a change of measure formula that expresses the selective likelihood in terms of an integral over variables appearing in the optimization problem. The region of integration can often be interpreted geometrically in terms of the normal cycle of the balls in the corresponding penalty. Using this change of measure\, we give a brief description of “inferactive data analysis”\, so-named to denote an interactive approach to data analysis with an emphasis on inference after data analysis.\nThis is joint work with Xiaoying Tian\, Jelena Markovic\, Snigdha Panigrahi and Nan Bi. \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-jonathan-taylor-stanford/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20171025T153000
DTEND;TZID=America/New_York:20171025T163000
DTSTAMP:20210515T194827
CREATED:20171012T192535Z
LAST-MODIFIED:20171012T192919Z
UID:3300-1508945400-1508949000@stat-or.unc.edu
SUMMARY:STOR Colloquium: Holger Rootzén\, Chalmers University of Technology
DESCRIPTION:Human life is unlimited — but short \n \nDoes the human lifespan have an impenetrable biological upper limit which ultimately will stop further increase in life lengths? Answers to this question are important for our understanding of the aging process\, and for the organization of society\, and have led to intense controversies. Demographic data for humans have been interpreted as showing existence of a limit close to the age\, 122.45 years\, of the longest living documented human\, Jeanne Calment\, or even as indication of a decreasing limit\, but also as evidence that a limit does not exist. This talk uses EVS\, extreme value statistics\, to study what data says about human mortality after age 110. We show that in North America\, Western Europe\, and Japan the yearly probability of dying after age 110 is constant and about 53% per year. Hence there is no finite limit to the human lifespan. Still\, given the present stage of biotechnology\, it is unlikely that during the next 25 years anyone will live longer than 128 years in these countries. Data\, remarkably\, show little difference in mortality after age 110 between men and women\, between earlier and later periods\, between ages\, or between persons with different lifestyles or genetic backgrounds. These results can help testing biological theories of aging and aid early confirmation of success of efforts to find a cure for aging. \n \nThis is joint work with Dmitrii Zholud. \n \n \n \n \n \nRefreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall
URL:https://stat-or.unc.edu/event/stor-colloquium-holger-rootzen-chalmers-university-of-technology/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20171106T143000
DTEND;TZID=America/New_York:20171106T153000
DTSTAMP:20210515T194827
CREATED:20170829T165906Z
LAST-MODIFIED:20171030T195736Z
UID:3128-1509978600-1509982200@stat-or.unc.edu
SUMMARY:STOR Colloquium; Xiao-Li Meng\, Harvard
DESCRIPTION:Dissecting Multiple Imputation from a Multi-phase Inference Perspective: \nWhat Happens When God’s\, Imputer’s and Analyst’s Models Are Uncongenial? \n \nXiao-Li Meng \nDepartment of Statistics\, Harvard University \n \nThis talk is based on a discussion paper (Xia and Meng\, Statistica Sinica\, 2017\, pp1485-1594) with the same title and the following abstract: \n \n“Real-life data are almost never really real. By the time the data arrive at an investigator’s desk or disk\, the raw data\, however defined\, have most likely gone through at least one “cleaning” process\, such as standardization\, re-calibration\, imputation\, or de-sensitization. Dealing with such a reality scientifically requires a more holistic multi-phase perspective than is permitted by the usual framework of “God’s model versus my model.” This article provides an in-depth look\, from this broader perspective\, into multiple-imputation (MI) inference (Rubin (1987)) under uncongeniality (Meng (1994)). We present a general estimating-equation decomposition theorem\, resulting in an analytic (asymptotic) description of MI inference as an integration of the knowledge of the imputer and the analyst\, and establish a characterization of self-efficiency (Meng (1994)) for regulating estimation procedures. These results help to reveal how the quality of and relationship between the imputer’s model and analyst’s procedure affect MI inference\, including how a seemingly perfect procedure under the “God-versus-me” paradigm is actually inadmissible when God’s\, imputer’s\, and analyst’s models are uncongenial to each other. Our theoretical investigation also leads to useful procedures that are as trivially implementable as Rubin’s combining rules\, yet with confidence coverage guaranteed to be minimally the nominal level\, under any degree of uncongeniality. We reveal that the relationship is very complex between the validity of approaches taken for individual phases and the validity of the final multi-phase inference\, and indeed that it is a nontrivial matter to quantify or even qualify the meaning of validity itself in such settings. These results and many open problems are presented to raise the general awareness that the multi-phase inference paradigm is an uncongenial forest populated by thorns\, as well as some fruits\, many of which are still low-hanging.”
URL:https://stat-or.unc.edu/event/stor-colloquium-xiao-li-meng-harvard/
LOCATION:Hanes 120
CATEGORIES:STOR Colloquium
END:VEVENT
END:VCALENDAR