Keynote speakers

Name: Vittorio Maniezzo, University of Bologna,Italy

Title: Machine Learning and combinatorial optimization, some posible catalytic effects

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Abstract: 

We are all quite aware of the foundational status of general optimization for Machine Learning (ML) and its ubiquity in ML algorithms. In this talk, I will try to restrict attention to Combinatorial Optimization (CO) and to its bidirectional linkages with ML. Indeed, ML has emerged as a prospective area of investigation for operations research in general, and for CO in particular. Following the impressive boost in the effectiveness of deep learning models, new approaches have been proposed as frameworks to tackle combinatorial optimization problems using ML techniques, while OR conferences and workshops are featuring an ever-increasing number of events and contributions related to these new trends. The talk aims at presenting a tentative taxonomy of both the contributions of CO techniques, eventually included in ML solutions, and vice-versa of ML results as included in CO methods.

 

 

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