Group for Research in Decision Analysis

Clustering: An optimization perspective

Daniel Aloise Assistant Professor, Department of Computer Engineering, Polytechnique Montréal, Canada

Clustering is one of the main tasks in unsupervised machine learning. It consists in finding groups in the data so that the overall similarity among data records in the same group is maximized. In this talk, I present how the clustering problem can be approached by the most diverse exact and heuristic optimization techniques, in contexts as real-time decision-making and Big Data.

Click here to view the presentation.

Free entrance.
Welcome to everyone!