Topology, Geometry, and Data Seminar - Chao Chen

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April 12, 2016
4:00PM - 5:00PM
Location
Caldwell Lab 137

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Add to Calendar 2016-04-12 16:00:00 2016-04-12 17:00:00 Topology, Geometry, and Data Seminar - Chao Chen Title: Computing Critical Points of a High Dimensional Distribution via Graphical ModelsSpeaker: Chao Chen (CUNY)Abstract: The computation of persistent homology is challenging for high dimensional data. In this talk, I will discuss an alternative direction that I am currently pursuing. The idea starts with representing the high dimensional data using a concise probabilistic model, namely, the graphical model. Next, we directly compute the critical points on the underlying graph instead of building a discretization of the domain. I will discuss different methods, e.g., dynamic programming, heuristic search and local neighborhood search, to compute local maxima and their attractive basins. I will also discuss the computation of saddle points. These methods have been used in making multiple diverse predictions and in clustering.Seminar URL: https://research.math.osu.edu/tgda/tgda-seminar.html  Caldwell Lab 137 Department of Mathematics math@osu.edu America/New_York public
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Title: Computing Critical Points of a High Dimensional Distribution via Graphical Models

Speaker: Chao Chen (CUNY)

Abstract: The computation of persistent homology is challenging for high dimensional data. In this talk, I will discuss an alternative direction that I am currently pursuing. The idea starts with representing the high dimensional data using a concise probabilistic model, namely, the graphical model. Next, we directly compute the critical points on the underlying graph instead of building a discretization of the domain. I will discuss different methods, e.g., dynamic programming, heuristic search and local neighborhood search, to compute local maxima and their attractive basins. I will also discuss the computation of saddle points. These methods have been used in making multiple diverse predictions and in clustering.

Seminar URL: https://research.math.osu.edu/tgda/tgda-seminar.html

 

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