Helsinki Algorithms Seminar: Michael Mathioudakis, University of Helsinki "Coresets for k-Means clustering"
Coresets for k-Means clustering
University of Helsinki
Coresets are compact representations of data, accompanied with a guarantee that models trained on them have competitive performance with models trained on all the data. In this talk, I will discuss state-of-the-art algorithms on coresets for k-Means by Bachem et.al. , presented earlier this year at the KDD conference.
 Bachem, Olivier, Mario Lucic, and Andreas Krause. "Scalable k-Means Clustering via Lightweight Coresets." International Conference on Knowledge Discovery and Data Mining (KDD). 2018.
Helsinki Algorithms Seminar is a weekly meeting of researchers in the Helsinki area interested in the art of algorithms and algorithm design, broadly interpreted to cover both theoretical ideas and algorithm engineering on concrete computing platforms. In most cases we have a presentation prepared for each meeting to communicate an idea, a recent result, work-in-progress, or demo, but this should not be at the expense of discussion and simply having fun with algorithms.
Our affiliations are with Aalto University and the University of Helsinki, and accordingly our activities alternate between the Otaniemi Campus of Aalto University and the Kumpula Campus of University of Helsinki, catalyzed by the Helsinki Institute for Information Technology HIIT, under the Algorithmic Data Analysis (ADA) programme.
For the season programme, please see the seminar webpage.