Wednesday 18 November 2015 h. 14:30, Room 2BC30
Michele Donini (Padova, Dip. Mat.)
"Learning with Kernels"
To solve a problem on a computer, we need an algorithm, which is a sequence of instructions that should be carried out to transform the input into the output. For some tasks, we do not have an algorithm: we know what the input is, we know what the output should be but we do not know how to transform the input into the output. What we lack in knowledge, we make up for in data. We can exploit data to "learn" using a Machine Learning algorithm, that is able to extract automatically the algorithm for the task.
In this talk, we give an introduction to a family of Machine Learning algorithms called Kernel Methods, starting from a general introduction to the Machine Learning problems and its purposes. After building up the fundamental tools of learning with kernels, we will introduce the principal ideas behind this family of algorithms and its ability to learn automatically using data.