Algorithms & Complexity


Clustering refers to the partitioning of a set of objects into groups (clusters) of similar objects. Due to its wide-spread applicability, it is among the most fundamental tasks in data analysis and unsupervised learning. Our goal is to design algorithms with provable guarantees, for example, with respect to running time, space consumption, or quality of the solution. Complementing this, we are also studying the limits of such algorithms.