Massive Data Models and Computational Geometry II

The last decade has seen an explosion of available data. To analyze the enormous amount of accrued data, classical algorithms are often not appropriate: the data may not be accessible in its entirety (but perhaps only in an aggregate form) and computations may need to be distributed or done in an online setting. The data often comes with an additional geometric flavor, either from applications or from mapping the data to feature spaces.

The workshop will focus on three classes of algorithms for dealing with massive geometric data, namely, streaming, distributed, and sublinear algorithms. The aim of the workshop is to identify and explore new research directions at the interface of massive data models and computational geometry.

This is an invitation-only workshop.

© Benedikt Kolbe