Dr. Vladimir (Vlad) Estivill-Castro

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Project I: Approximate Proximity for Applications in Data Mining and Visualization

Aims:
(1) a better theoretical understanding of algorithmic approximation to exact proximity information,
(2) practical heuristics for the clustering problem in data mining, based on techniques for approximation of proximity information and parameterized complexity, for large spatial and categorical data sets, and
(3) practical methods for real-time graph layout in 2D and 3D, based on approximations to proximity information and parameterized complexity.

Colaborators: Michael Fellows and Mike Houle

Funding: ARC Discovery grant