Tyler Whitehouse
In this talk we discuss some curvatures for simplices based on multi-way generalizations of the ordinary sine function. Specifically we how such curvatures can be used to estimate least squares errors for probability measures on Euclidean spaces, as well as how they can be used for certain clustering problems for which pair-wise affinities are not effective. Finally, we clarify the meaning of the term ``quantitative geometry'' with a specific example called d-separation.
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