Unless otherwise noted, all talks are in 120 Hanes Hall, at 3:30 PM on Mondays. 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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October 2017

STOR Colloquium: Srinagesh Gavirneni, Cornell

October 16, 2017 @ 3:30 pm - 4:30 pm

Title: Co-opetition in Service Clusters with Waiting-Area Entertainment  Link to paper:  Co-opetition-Service-Clusters Abstract: 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…

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STOR Colloquium: Jonathan Taylor, Stanford

October 23, 2017 @ 3:30 pm - 4:30 pm

Selective sampling after solving a convex problem   Recent 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…

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STOR Colloquium: Holger Rootzén, Chalmers University of Technology

October 25, 2017 @ 3:30 pm - 4:30 pm

Human life is unlimited -- but short   Does 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…

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November 2017

STOR Colloquium; Xiao-Li Meng, Harvard

November 6, 2017 @ 3:30 pm - 4:30 pm

Dissecting Multiple Imputation from a Multi-phase Inference Perspective: What Happens When God's, Imputer's and Analyst's Models Are Uncongenial?   Xiao-Li Meng Department of Statistics, Harvard University   This talk is based on a discussion paper (Xia and Meng, Statistica Sinica, 2017, pp1485-1594) with the same title and the following abstract:   “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…

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STOR Colloquium: Danica Ommen, Iowa State University

November 13, 2017 @ 3:30 pm - 4:30 pm

Title: Different Paradigms of Interpretation for Forensic Value of Evidence Quantification Abstract: Currently, one of the major problems in the forensic science community is the confusion between different statistical paradigms. A quantification of the value of evidence is interpreted differently under each paradigm, and may even be the answer to different questions. It is our opinion that these issues need to be addressed before quantitative forensic analyses are considered a reliable science in the justice system. A related issue is the…

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STOR Colloquium: Todd Kuffner, Washington University in St. Louis

November 15, 2017 @ 3:30 pm - 4:30 pm

Title: Philosophy of Science, Principled Statistical Inference, and Data Science   Abstract: Statistical reasoning and statistical inference have strong historical connections with philosophy of science. In this talk, the new paradigm of data-driven science is examined through comparison with principled statistical approaches. I will review the merits and shortcomings of principled statistical inference. The talk will feature a case study of post-selection inference, recent progress regarding inference for black box algorithms, and a survey of future challenges.   Refreshments will…

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STOR Colloquium: Alex Belloni, Duke

November 20, 2017 @ 3:30 pm - 4:30 pm

Title: Inference with High-Dimensional Controls and Parameters of Interest based on joint work with Victor Chernozhukov, Denis Chetverikov, and Ying Wei Abstract: In this work we propose and analyze procedures to construct confidence regions for p (infinite dimensional) parameters of interest after model selection for general moment condition models where p is potentially larger than the sample size n. This allows us to cover settings with functional response data where each of the p > n parameters of interest is…

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December 2017

STOR Colloquium: Anru Zhang, University of Wisconsin-Madison

December 4, 2017 @ 3:30 pm - 4:30 pm

Singular Value Decomposition for High-dimensional High-order Data   High-dimensional high-order data arise in many modern scientific applications including genomics, brain imaging, and social science. In this talk, we consider the methods, theories and computations for tensor singular value decomposition (tensor SVD), which aims to extract the hidden low-rank structure from high-dimensional high-order data. First, comprehensive results are developed on both the statistical and computational limits for tensor SVD under the general scenario. This problem exhibits three different phases according to…

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January 2018

Mariana Olvera-Cravioto, University of California, Berkeley

January 10 @ 3:30 pm - 4:30 pm

Efficient simulation for branching recursions   A variety of problems in science and engineering, ranging from population and statistical physics models to the study of queueing systems, computer networks and the internet, lead to the analysis of branching distributional equations. The solutions to these equations are not in general analytically tractable, and hence need to be computed numerically. This talk discusses a simulation algorithm known as “Population Dynamics”, which is designed to produce a pool of identically distributed observations having…

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CANCELLED: Jie Ding, Harvard University

January 17 @ 3:30 pm - 4:30 pm

Some New Foundational Principles and Fast Algorithms in Data Analytics   Rapid developments in communications, networking, AI robots, 3D printing, genomics, blockchain, novel materials, and powerful computation platforms are rapidly bringing data-generating people, processes and devices together. The interactions between data analytics in multiple regimes (sparse, panel, big data, etc.) and other fields are exciting because the tools that are being invented now may enable new, faster and semi-automated methods of scientific discovery. These, in turn, might further amplify the…

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