Mittagsseminar (in cooperation with A. Steger, D. Steurer and B. Sudakov)

Date and Time: Thursday, March 06, 2014, 12:15 pm

Duration: 30 minutes

Location: OAT S15/S16/S17

Speaker: Shai Ben-David (University of Waterloo)

Theoretical foundations of clustering - few results and many challenges

Clustering is a basic data mining task with a wide variety of applications. However, clustering is an ill defined problem. Clustering does not have a well defined ground truth - given a data set, it is not clear what a “correct” clustering for that set is. Indeed, different algorithms may yield dramatically different outputs for the same input sets.

Faced with a concrete clustering task, a user needs to choose an appropriate clustering algorithm, as well as a concrete setting for the tunable parameters of the chosen algorithm. Currently, such decisions are often made in a very ad hoc, if not completely random, manner. Given the crucial effect of the choice of a clustering algorithm on the resulting clustering, this state of affairs is truly regrettable. Can the research community develop effective tools for helping users make informed decisions when they come to pick a clustering tool for their data?

In this talk I will survey theoretical research in that direction, as well as outline other major open problems and challenges for the developing theory of clustering.

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