Journées de l'optimisation 2016

HEC Montréal, Québec, Canada, 2 — 4 mai 2016

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WAP Séance plénière V / Plenary Session V

4 mai 2016 09h00 – 10h00

Salle: Amphithéâtre Banque Nationale

Présidée par Dominique Orban

1 présentation

  • 09h00 - 10h00

    On big data, optimization and learning

    • Andrea Lodi, prés., Polytechnique Montreal

    In this talk I review a couple of applications on Big Data that I personally like and I try to explain my point of view as a Mathematical Optimizer -- especially concerned with discrete (integer) decisions -- on the subject. I advocate a tight integration of Machine Learning and Mathematical Optimization (among others) to deal with the challenges of decision-making in Data Science. For such an integration I try to answer three questions: 1) what can optimization do for machine learning? 2) what can machine learning do for optimization? 3) which new applications can be solved by the combination of machine learning and optimization?

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