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DTSTART;TZID=America/New_York:20220203T145700
DTEND;TZID=America/New_York:20220203T165700
DTSTAMP:20240301T105825Z
CREATED:20240215T092602Z
LAST-MODIFIED:20240301T105825Z
UID:10002717-1643900220-1643907420@cmsa.fas.harvard.edu
SUMMARY:2/3/2022 – Interdisciplinary Science Seminar
DESCRIPTION:Title:Quasiperiodic prints from triply periodic blocks \nAbstract: Slice a triply periodic wooden sculpture along an irrational plane. If you ink the cut surface and press it against a page\, the pattern you print will be quasiperiodic. Patterns like these help physicists see how metals conduct electricity in strong magnetic fields. I’ll show you some block prints that imitate the printing process described above\, and I’ll point out the visual features that reveal conductivity properties. \nInteractive slides:https://www.ihes.fr/~fenyes/seeing/slices/
URL:https://cmsa.fas.harvard.edu/event/2-3-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/CMSA-Interdisciplinary-Science-Seminar-2.03.2022-1583x2048-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220210T150000
DTEND;TZID=America/New_York:20220210T160000
DTSTAMP:20240301T105720Z
CREATED:20240215T092349Z
LAST-MODIFIED:20240301T105720Z
UID:10002716-1644505200-1644508800@cmsa.fas.harvard.edu
SUMMARY:2/10/2022 – Interdisciplinary Science Seminar
DESCRIPTION:Title: Metric Algebraic Geometry \nAbstract: A real algebraic variety is the set of points in real Euclidean space that satisfy a system of polynomial equations. Metric algebraic geometry is the study of properties of real algebraic varieties that depend on a distance metric. In this talk\, we introduce metric algebraic geometry through a discussion of Voronoi cells\, bottlenecks\, and the reach of an algebraic variety. We also show applications to the computational study of the geometry of data with nonlinear models.
URL:https://cmsa.fas.harvard.edu/event/2-10-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Interdisciplinary-Science-Seminar-2.10.2022-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220217T150500
DTEND;TZID=America/New_York:20220217T160500
DTSTAMP:20240301T105602Z
CREATED:20240215T092142Z
LAST-MODIFIED:20240301T105602Z
UID:10002714-1645110300-1645113900@cmsa.fas.harvard.edu
SUMMARY:Sparse Markov Models for High-dimensional Inference
DESCRIPTION:Abstract: Finite order Markov models are theoretically well-studied models for dependent data.  Despite their generality\, application in empirical work when the order is larger than one is quite rare.  Practitioners avoid using higher order Markov models because (1) the number of parameters grow exponentially with the order\, (2) the interpretation is often difficult. Mixture of transition distribution models (MTD)  were introduced to overcome both limitations. MTD represent higher order Markov models as a convex mixture of single step Markov chains\, reducing the number of parameters and increasing the interpretability. Nevertheless\, in practice\, estimation of MTD models with large orders are still limited because of curse of dimensionality and high algorithm complexity. Here\, we prove that if only few lags are relevant we can consistently and efficiently recover the lags and estimate the transition probabilities of high order MTD models. Furthermore\, we show that using the selected lags we can construct non-asymptotic confidence intervals for the transition probabilities of the model. The key innovation is a recursive procedure for the selection of the relevant lags of the model.  Our results are  based on (1) a new structural result of the MTD and (2) an improved martingale concentration inequality. Our theoretical results are illustrated through simulations.
URL:https://cmsa.fas.harvard.edu/event/2-17-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
ATTACH;FMTTYPE=image/jpeg:https://cmsa.fas.harvard.edu/media/CMSA-Interdisciplinary-Science-Seminar-2.17.2022-1-1583x2048-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220224T150800
DTEND;TZID=America/New_York:20220224T160800
DTSTAMP:20240301T104857Z
CREATED:20240215T091941Z
LAST-MODIFIED:20240301T104857Z
UID:10002713-1645715280-1645718880@cmsa.fas.harvard.edu
SUMMARY:Singular Set in Obstacle Problems
DESCRIPTION:Abstract: In this talk we describe a new method to study the singular set in the obstacle problem. This method does not depend on monotonicity formulae and works for fully nonlinear elliptic operators. The result we get matches the best-known result for the case of Laplacian.
URL:https://cmsa.fas.harvard.edu/event/2-24-2022-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
ATTACH;FMTTYPE=image/png:https://cmsa.fas.harvard.edu/media/CMSA-Interdisciplinary-Science-Seminar-2.24.2022-1583x2048-1.png
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