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Statistics and Data Science Seminar Eric Kolaczyk (Boston University)

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Women in Data Science (WiDS) Conference

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Statistics and Data Science Seminar Aditya Guntuboyina (UC Berkley)

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IDSS Special Seminar Timnit Gebru (Google)

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Statistics and Data Science Seminar Alex Belloni (Duke University)

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Statistics and Data Science Seminar Eliran Subag (New York University)

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Why Aren’t Network Statistics Accompanied By Uncertainty Statements?

Eric Kolaczyk (Boston University)
E18-304

Abstract: Over 500K scientific articles have been published since 1999 with the word “network” in the title. And the vast majority of these report network summary statistics of one type or another. However, these numbers are rarely accompanied by any quantification of uncertainty. Yet any error inherent in the measurements underlying the construction of the…

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Women in Data Science (WiDS) Conference

Microsoft NERD Center

This one-day technical conference will bring together local academic leaders, industrial professionals, and students to hear about the latest data science related research in a number of domains, to learn how leading-edge companies are leveraging data science for success, and to connect with potential mentors, collaborators, and others in the field. The program will include…

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Univariate total variation denoising, trend filtering and multivariate Hardy-Krause variation denoising

Aditya Guntuboyina (UC Berkley)
E18-304

Abstract: Total variation denoising (TVD) is a popular technique for nonparametric function estimation. I will first present a theoretical optimality result for univariate TVD for estimating piecewise constant functions. I will then present related results for various extensions of univariate TVD including adaptive risk bounds for higher-order TVD (also known as trend filtering) as well…

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Using Computer Vision to Study Society: Methods and Challenges

Timnit Gebru (Google)
32-G449: Patil/Kiva Seminar Room

Abstract: Targeted socio-economic policies require an accurate understanding of a country's demographic makeup. To that end, the United States spends more than 1 billion dollars a year gathering census data such as race, gender, education, occupation and unemployment rates. Compared to the traditional method of collecting surveys across many years which is costly and labor…

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Subvector Inference in Partially Identified Models with Many Moment Inequalities

Alex Belloni (Duke University)
E18-304

Abstract: In this work we consider bootstrap-based inference methods for functions of the parameter vector in the presence of many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. In particular this covers the case of subvector inference, such as the inference on a…

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Optimization of random polynomials on the sphere in the full-RSB regime

Eliran Subag (New York University)
E18-304

Abstract: The talk will focus on optimization on the high-dimensional sphere when the objective function is a linear combination of homogeneous polynomials with standard Gaussian coefficients. Such random processes are called spherical spin glasses in physics, and have been extensively studied since the 80s. I will describe certain geometric properties of spherical spin glasses unique…

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MIT Statistics + Data Science Center
Massachusetts Institute of Technology
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Cambridge, MA 02139-4307
617-253-1764