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.
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Welcome to everyone!
Université de Montréal Campus