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Euclidean Embeddings of Snowflake Metric Spaces

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by Marie Snipes Kenyon College

What
  • Analysis Seminar
When Fri, Sep 25, 2015
from 04:00 PM to 05:00 PM
Where Ritter Hall 229
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Metric spaces are useful tools for modeling sets of objects where there is a natural notion of distance; examples include geographical data, genetic data, and signals (like sound waves or images).  We often seek to classify metric spaces by how Euclidean they look: specifically, we want to know if some metric space can be embedded in Euclidean space.  In this talk we will use examples to introduce the general embedding problem.  We will then discuss a theorem by Assouad guaranteeing bi-Lipschitz embeddings of so-called snowflake metric spaces into Euclidean space and some related work by Naor-Nieman and David-Snipes.

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