Geometric Computing over Uncertain Data
published: Oct. 2, 2012, recorded: September 2012, views: 3315
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Geometric structures such as the convex hull, Delaunay triangulation, or minimum spanning tree (MST) are fundamental tools for reasoning about multi-dimensional data. What happens to these structures when the underlying data points are known with only partial certainty? For instance, what is the expected cost of the MST of a set of points, each known to be alive with some probability? Or, in a set of uncertain points, how likely is it that the closest pair is within distance L? This talk explores the effects of data uncertainty on the complexity of basic geometric problems.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !