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Sampling from the SK measure via algorithmic stochastic localization

Ahmed El Alaoui (Cornell University)
E18-304

Abstract: I will present an algorithm which efficiently samples from the Sherrington-Kirkpatrick (SK) measure with no external field at high temperature. The approach is based on the stochastic localization process of Eldan, together with a subroutine for computing the mean vectors of a family of SK measures tilted by an appropriate external field. This approach is general and can potentially be applied to other discrete or continuous non-log-concave problems. We show that the algorithm outputs a sample within vanishing rescaled Wasserstein…

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Inference in High Dimensions for (Mixed) Generalized Linear Models: the Linear, the Spectral and the Approximate

Marco Mondelli (Institute of Science and Technology Austria)
E18-304

Abstract: In a generalized linear model (GLM), the goal is to estimate a d-dimensional signal x from an n-dimensional observation of the form f(Ax, w), where A is a design matrix and w is a noise vector. Well-known examples of GLMs include linear regression, phase retrieval, 1-bit compressed sensing, and logistic regression. We focus on the high-dimensional setting in which both the number of measurements n and the signal dimension d diverge, with their ratio tending to a fixed constant.…

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SES PhD Admissions Q&A

Fotini Christia (IDSS)
online

Learn about the Social and Engineering Systems Doctoral Program. Hosted by SES Program Head, Prof. Fotini Christia This live Q&A is a follow-up session for the pre-recorded SES Admissions Webinar which should be viewed prior to attending the Q&A. Sign-up by 9 November, 12PM EDT.

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Virtual Recruitment Fair

Online

On November 15th, 2022, IDSS participates in a virtual recruitment fair focused on recruiting scholars historically underrepresented in engineering. The fair is hosted by the School of Engineering and Office for Graduate Education (OGE).

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GradCatalyst: SES

Hammaad Adam, Hussein Mozannar, Erin Walk, Aurora Zhang (IDSS)
online

Join the MIT Office of Graduate Education for an MIT student-led workshop for undergraduates planning on graduate school.

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Distance-based summaries and modeling of evolutionary trees.

Julia Palacios (Stanford University)
E18-304

Abstract:  Phylogenetic trees are mathematical objects of great importance used to model hierarchical data and evolutionary relationships with applications in many fields including evolutionary biology and genetic epidemiology. Bayesian phylogenetic inference usually explore the posterior distribution of trees via Markov Chain Monte Carlo methods, however assessing uncertainty and summarizing distributions remains challenging for these types of structures. In this talk I will first introduce a distance metric on the space of unlabeled ranked tree shapes and genealogies. I will then…

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SES PhD Admissions Q&A

Fotini Christia (IDSS)
online

Learn about the Social and Engineering Systems Doctoral Program. Hosted by SES Program Head, Prof. Fotini Christia This live Q&A is a follow-up session for the pre-recorded SES Admissions Webinar which should be viewed prior to attending the Q&A. Sign-up by 28 November, 12PM EDT.

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Coding convex bodies under Gaussian noise, and the Wills functional

Jaouad Mourtada (ENSAE Paris)
E18-304

Abstract: We consider the problem of sequential probability assignment in the Gaussian setting, where one aims to predict (or equivalently compress) a sequence of real-valued observations almost as well as the best Gaussian distribution with mean constrained to a general domain. First, in the case of a convex constraint set K, we express the hardness of the prediction problem (the minimax regret) in terms of the intrinsic volumes of K. We then establish a comparison inequality for the minimax regret…

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