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Short Stories about Data and Sports

Anette "Peko" Hosoi (MIT)

ABSTRACT Recent advances in data collection have made sports an attractive testing ground for new analyses and algorithms, and a fascinating controlled microcosm in which to explore social interactions. In this talk I will describe two studies in this arena: one related to public health and the pandemic and one related to decision-making in basketball.  In the first, I will discuss what can be learned from the natural experiments that were (fortuitously) run in America football stadiums. During the 2020…

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SES Dissertation Defense

Yi "Alicia" Sun (IDSS)

Algorithmic Fairness in Sequential Decision Making ABSTRACT Machine learning algorithms have been used on a wide range of applications, and there are growing concerns about potential biases of those algorithms. While many solutions have been proposed for addressing biases in predictions from an algorithm, there is still a gap in translating predictions to a justified decision. Moreover, even a justified and fair decision could lead to undesirable consequences with decisions create a feedback effect. While numerous solutions have been proposed…

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Democracy and the Pursuit of Randomness

Ariel Procaccia (Harvard University)
E18-304 Abstract: Sortition is a storied paradigm of democracy built on the idea of choosing representatives through lotteries instead of elections. In recent years this idea has found renewed popularity in the form of citizens’ assemblies, which bring together randomly selected people from all walks of life to discuss key questions and deliver policy recommendations. A principled approach to sortition, however, must resolve the tension between two competing requirements: that the demographic composition of citizens’ assemblies reflect the general population…

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Regularized modified log-Sobolev inequalities, and comparison of Markov chains

Konstantin Tikhomirov (Georgia Institute of Technology)

Abstract: In this work, we develop a comparison procedure for the Modified log-Sobolev Inequality (MLSI) constants of two reversible Markov chains on a finite state space. As an application, we provide a sharp estimate of the MLSI constant of the switch chain on the set of simple bipartite regular graphs of size n with a fixed degree d. Our estimate implies that the total variation mixing time of the switch chain is of order O(n log(n)). The result is optimal up to a multiple…

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Efficient derivative-free Bayesian inference for large-scale inverse problems

Jiaoyang Huang (University of Pennsylvania)

Abstract: We consider Bayesian inference for large-scale inverse problems, where computational challenges arise from the need for the repeated evaluations of an expensive forward model, which is often given as a black box or is impractical to differentiate. In this talk I will propose a new derivative-free algorithm Unscented Kalman Inversion, which utilizes the ideas from Kalman filter, to efficiently solve these inverse problems. First, I will explain some basics about Variational Inference under general metric tensors. In particular, under the…

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Disinformation and free speech: perspectives on the future of information

Hayden Library and online

A panel of experts from a range of disciplines will share their perspectives on how fact, fiction, and opinion converge, diverge, and occasionally collide. Based on their research, the speakers will share their views on how access to accurate information aligns with free speech; how we can help people evaluate information; and much more. Panelists: Adam Berinsky, Mitsui Professor of Political Science and Director of the MIT Political Experiments Research Lab David Karger, Professor of Computer Science and member of…

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MIT Policy Hackathon 2022: A New (Re)generation

MIT Policy Hackathon is a 48-hour hackathon convened by students from MIT’s Institute for Data, Systems, and Society and the MIT Technology and Policy Program that aims to address some of today’s most relevant societal challenges. Applications received by September 25 will be give priority. Applications received up until October 1, will be reviewed on a rolling basis until the remaining spots are filled. Apply today!

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MIT Computing Virtual Grad Fair


Join IDSS's Social and Engineering Systems Doctoral Program (SES), Technology and Policy Program (TPP), and Interdisciplinary Doctoral Program in Statistics (IDPS) at the inaugural MIT Schwarzman College of Computing Virtual Grad School Fair: Academic Programs Showcase. The MIT Schwarzman College of Computing is home to some of the world’s most well-known programs in their field, including a variety of computationally-intensive graduate programs. In these specialized programs, students and faculty address challenging multifaceted problems using data, computational methods, and a host of…

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Maximum likelihood for high-noise group orbit estimation and cryo-EM

Zhou Fan (Yale University)

Abstract: Motivated by applications to single-particle cryo-electron microscopy, we study a problem of group orbit estimation where samples of an unknown signal are observed under uniform random rotations from a rotational group. In high-noise settings, we show that geometric properties of the log-likelihood function are closely related to algebraic properties of the invariant algebra of the group action. Eigenvalues of the Fisher information matrix are stratified according to a sequence of transcendence degrees in this invariant algebra, and critical points…

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SES & TPP @ Georgia Tech Virtual Graduate School Showcase


Georgia Tech invites all students interested in applying to graduate school to attend their Virtual Graduate Showcase.  Staff from IDSS programs,  Technology and Policy Program (TPP) and the Doctoral Program in Social and Engineering  Systems (SES) will be there to answer your questions about the application process and the program from 1:00 — 3:00 p.m. Learn more about the fair and register for free.

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