Machine learning and combinatorial optimization, editorial

Statistical Machine Learning and Combinatorial Optimization

Guest Editorial: Advanced Combinatorial Optimization and Applications

Biographical notes: Dr. Said Ben Messaoud received his Diploma of “Maîtrise” in Applied Mathematics from the Faculty of Sciences of Monastir in 1998, his MS degree from the INPGGrenoble, in 2000 and his PhD degree in Optimization in 2004 from the Technology University of Troyes. He is a Assistant Professor at the Higher Institute for Informatics and Mathematics of Monastir-Tunisia. His research...

Considering Stochastic and Combinatorial Optimization

Here, issues connected with characteristic stochastic practices are considered. In the first part, the plausibility of covering the arrangements of an improvement issue on subjective subgraphs is studied. The impulse for this strategy is a state where an advancement issue must be settled as often as possible for discretionary illustrations. Then, a preprocessing stage is considered that would q...

Machine Learning and Optimization

This final project attempts to show the differences of machine learning and optimization. In particular while optimization is concerned with exact solutions machine learning is concerned with generalization abilities of learners. We present examples in the areas of classification and regression where this difference is easy to observe as well as theoretical reasons of why this two areas are dif...

Combinatorial Optimization on a Boltzmann Machine

We discuss the problem of solving (approximately) combinatorial optimization problems on a Boltzmann machine. It is shown for a number of combinatorial optimization problems how they can be mapped directly onto a Boltzmann machine by choosing appropriate connection patterns and connection strengths. In this way maximizing the consensus in the Boltzmann machine is equivalent to finding an optima...