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December 2020

A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Net

Rong Ge - Duke University

December 4, 2020 @ 11:00 am - 12:00 pm
online

Abstract: The training of neural networks optimizes complex non-convex objective functions, yet in practice simple algorithms achieve great performances. Recent works suggest that over-parametrization could be a key ingredient in explaining this discrepancy. However, current theories could not fully explain the role of over-parameterization. In particular, they either work in a regime where neurons don't move much, or require large number of neurons. In this paper we develop a local convergence theory for mildly over-parameterized two-layer neural net. We show…

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Mass Incarceration and the Challenge of Social Research

Bruce Western (Columbia University)

December 7, 2020 @ 4:00 pm - 5:00 pm
Online

IDSS will host Prof. Bruce Western as part of the Distinguished Speaker Seminar series. Prof. Westerns research has examined the causes, scope, and consequences of the historic growth in U.S. prison populations. He is Co-Director of the Justice Lab at Columbia University.

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January 2021

Data Science and Big Data Analytics: Making Data Driven Decisions

January 25
Online

Developed by 10 MIT faculty members at IDSS, this seven-week course is specially designed for data scientist, business analyst, engineers and technical managers looking to learn the latest theories and strategies to harness data. Offered by MIT xPRO.

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February 2021

Understanding Cultural Persistence and Change

Nathan Nunn (Harvard University)

February 2 @ 3:00 pm - 4:00 pm
Online

Please join us on Tuesday, February 2, 2021 at 3:00pm for the Distinguished Speaker Seminar with Nathan Nunn, Frederic E. Abbe Professor of Economics at Harvard University.

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MIT Sports Summit 2021

February 4 - February 5
online

The MIT Sports Lab invites you to the MIT Sports Summit 2021, a virtual event hosted on Thursday, Feb. 4th and Friday, Feb. 5th! It is an opportunity for the MIT community to interface with the Sports Lab’s affiliates and partners, sharing advances, challenges, and passions at the intersection of engineering and sports. We are featuring talks from leaders in industry and academia, as well as interactive sessions showcasing student research posters and sports tech startups. This is an invitation-only event for current MIT community…

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Faster and Simpler Algorithms for List Learning

Jerry Li, Microsoft Research

February 19 @ 11:00 am - 12:00 pm
online

Abstract: The goal of list learning is to understand how to learn basic statistics of a dataset when it has been corrupted by an overwhelming fraction of outliers. More formally, one is given a set of points $S$, of which an $\alpha$-fraction $T$ are promised to be well-behaved. The goal is then to output an $O(1 / \alpha)$ sized list of candidate means, so that one of these candidates is close to the true mean of the points in $T$.…

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Self-regularizing Property of Nonparametric Maximum Likelihood Estimator in Mixture Models

Yury Polyanskiy, MIT

February 26 @ 11:00 am - 12:00 pm
online

Abstract: Introduced by Kiefer and Wolfowitz 1956, the nonparametric maximum likelihood estimator (NPMLE) is a widely used methodology for learning mixture models and empirical Bayes estimation. Sidestepping the non-convexity in mixture likelihood, the NPMLE estimates the mixing distribution by maximizing the total likelihood over the space of probability measures, which can be viewed as an extreme form of over parameterization. In this work we discover a surprising property of the NPMLE solution. Consider, for example, a Gaussian mixture model on…

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March 2021

IDSS Distinguished Speaker Seminar with Brigitte Madrian (Brigham Young University)

Brigitte Madrian (Brigham Young University)

March 2 @ 3:00 pm - 4:00 pm
Online

Please join us on Tuesday, March 2, 2021 at 3:00pm for the Distinguished Speaker Seminar with Brigitte Madrian (Brigham Young University)

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UTEC-IDSS MicroMasters in Statistics and Data Science Webinar

March 4 @ 5:00 pm - 6:00 pm
online

Join this joint webinar on March 4th to learn more about this blended learning Masters' program offered by UTEC (Universidad Tecnológica del Uruguay) with the academic support of the Institute for Data, Systems, and Society. 

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Detection Thresholds for Distribution-Free Non-Parametric Tests: The Curious Case of Dimension 8

Bhaswar B. Bhattacharya, UPenn Wharton

March 5 @ 11:00 am - 12:00 pm
online

Abstract: Two of the fundamental problems in non-parametric statistical inference are goodness-of-fit and two-sample testing. These two problems have been extensively studied and several multivariate tests have been proposed over the last thirty years, many of which are based on geometric graphs. These include, among several others, the celebrated Friedman-Rafsky two-sample test based on the minimal spanning tree and the K-nearest neighbor graphs, and the Bickel-Breiman spacings tests for goodness-of-fit. These tests are asymptotically distribution-free, universally consistent, and computationally efficient…

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