Author: Matteo Tiezzi Date: March, 2021 Topics: Learning by Constraints; Constraint optimization; Graph Neural Networks; Lifelong Learning. Abstract A crucial role for the success of the Artificial Neural Networks (ANN) processing scheme has been played by the feed-forward propagation of signals. The input patterns undergo a series of stacked parametrized transformations, which foster deep feature […]

PH.D. THESIS Author: Dario Zanca Date: March, 2019 Topics: Computational modeling of visual attention; Computer vision; Machine Learning. Abstract Visual attention is a crucial process for humans and foveated animals in general. The ability to select relevant locations in the visual field greatly simplifies the problem of vision. It allows a parsimonious management of the […]

Simplicity and elegance have always been incredibly useful criteria for the development of successful theories that describe natural phenomena. Variational methods frame this parsimony principles into precise mathematical statements. In this thesis we showed how we can formulate learning theories using calculus of variations. Despite the natural way in which learning problem can be formulated […]

Giannini’s thesis A key point in the success of machine learning, and in particular deep learning, has been the availability of high-performance computing architectures allowing to process a large amount of data. However, this potentially prevents a wider application of machine learning in real world applications, where the collection of training data is often a […]