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.
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
Starting from the paper “A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications”, by Marco Pietrosanto, Eugenio Mattei, Manuela Helmer-Citterich,Fabrizio Ferrè, Nucleic Acids Research, 2016 1, doi: 10.1093/nar/gkw750, we wish to explore
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 would like to look inside some classical statistical procedures (e.g., forecasting time series) from an optimization point of view. The aim is to use global optimization techniques to solve optimal estimation problems in statistics
Nvidia just donated a Titan X Pascal GPU to our Laboratory – we would like to experiment global optimization algorithms on this architecture. Skills required: python, possibly Cuda Candidate: Samuele Tamburi
Radio Base Stations (RBSs) are among the constitutive bricks of a mobile network, acting both as interfaces with end users and transmissive units. Each RBS belongs to a network operator, who in turn allows other operators to use the infrastructure
In the main Computer Science Engineering curricula at Florence University, Operations Research courses rank #1: Fondamenti di Ricerca Operativa (prof. Fabio Schoen): #1 course for the Laurea degree in Computer Science Engineering Optimization Methods (prof. Marco Sciandrone)
Feature selection can be performed by the Least Absolute Shrinkage and Selection Operator (LASSO), a regression method which imposes a penalty on the absolute value of the regression coefficients. LASSO presents some limitations since it can’t succeed in recovering the right set of features