This thesis is devoted to the re-implementation of a very large scale kernel ridge regression software tool and to its extension to the semi-supervised case Started: November 2018 Candidate: Enrico Civitelli Graduated: April 2019
Managing inventories when the demand is uncertain is a challenging problem involving forecasting, modeling and optimization. This thesis is devoted to the extension of classical models, like the newsvendor, to multiple products, integer order quantities, logical constraints, assortment, and other
This thesis is devoted to experiment numerical optimization techniques on the D-Wave quantum computer We will simulate some combinatorial optimization problems and try to find innovative problem mapping in order to fully exploit the capacity of the quantum annealing machine.
Based on a paper by D. Bertsimas, we experimented on discrete optimization algorithms for the optimal training of a decision tree. Assigned: July 2018, discussed December 2018 Student: Francesca Del Lungo
This thesis dealt with developing an optimization algorithm for health care staff planning, based on a real ward requirements. Required skills: linear programming, possibly python, Java or C++ Student: Giulia Forasassi (based on an initial model prepared by Ayca Sarikaya,
Hospital wards are faced with day-to-day necessity to accurately forecast the consumption of drugs in order not to under stock nor to have too large inventories. This thesis explores the capabilities of some time series and some machine learning tools
How to use information collected during past matches in order to be able to predict the final result of a match? This thesis explores machine learning methods and features extraction towards the goal of being able to anticipate the final result.
Despite the progress of medicine in recent decades, epilepsy is a disease whose knowledge is still limited. About one third of patients with this disease continue to present crises despite pharmacological treatments, surgical interventions, and the medical assistance. The most
by Cosimo Casini Planning the optimal trajectory of an interplanetary space mission allows to save large amounts of fuel and time. Such a task can be modelled as a constrained global optimization problem. However, solving the resulting model is extremely
We have got some data on students’ careers in the Engineerring school. We would like to apply some machine learning technique to find useful information inside. E.g., which part of the pre-admission test is correlated with the career? How to