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SUMMARY:AMS Weekly Seminar w/ Baba Vemuri (University of Florida) on Zoom
DESCRIPTION:Title: Nested Homogeneous Spaces: Construction\, Learning and Applications \nAbstract: Homogeneous space of a Lie Group G\, is a manifold M on which the group G acts transitively.\nIntuitively\, every point in a homogeneous space looks locally alike in the sense of an isometry\, diffeomorphism\nor a homeomorphism. Such spaces are abundant in practice e.g.\, the n-sphere\, Grassmanian\,\nhyperbolic space\, manifold of symmetric positive definite matrices etc. In statistics and machine learning\,\nprincipal component analysis is the de facto choice for dimensionality reduction and produces nested\nlinear subspaces. In this talk\, I will present a recipe for generalizing this concept of producing nested\nsubspaces to homogeneous spaces in general\, and show how this general recipe can be integrated into a\nlearning framework. Specific examples of dimensionality reduction and pattern classification using the\nnested homogeneous space model will be presented for the Grassmanian and the hyperbolic space. In the\nlatter case\, the nested hyperbolic space model will be used to develop a nested hyperbolic graph neural\nnetwork. Experimental results on a variety of synthetic and real data sets depicting the performance of\nthe models in comparison to the state-of-the-art will be interspersed throughout the presentation. \nHere is the zoom link is: https://wse.zoom.us/j/95448608570 \n
URL:https://engineering.jhu.edu/ams/event/ams-weekly-seminar-w-baba-vemuri-university-of-florida-on-zoom/
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