Machine Learning is a set of methods and techniques for constructing software systems automatically by analyzing only examples of the desired behaviour.
You do not write a program. You only provide examples of what you want. The program will be synthesized automatically.
In our lab we focus on engineering applications: have a look to our publications to know more about specific research topics.
The Machine Learning Lab is directed by prof. Alberto Bartoli, assisted by prof. Eric Medvet, and hosts PostDocs, PhD students and LM, LT students: check the opportunities.
The lab is located at Department of Engineering and Architecture (DIA), University of Trieste (room 1259, 2nd floor, building C3). We are on Twitter and Google+.
We have written an essay titled like this post that has been accepted for publication on The Information Society journal: Research evaluation, which is an increasingly pressing issue, invariably relies on citation counts. In this contribution we highlight two... – More
Just accepted at the prestigious ARES Conference 2014. The title says a lot of things: - We propose a system for continuous reauthentication of web users based on the observed mouse dynamics. The task of the system consists in continuously checking the... – More
We have just been notified that our latest work has been accepted at the prestigious "13th International Conference on Parallel Problem Solving from Nature (PPSN 2014)". The problem: The ability to generate security-related alerts while analyzing network... – More
Great news: our paper "Playing Regex Golf with Genetic Programming" has been accepted at ACM GECCO, the top conference on Evolutionary Computation (we were there also in 2013 and 2012, though!). What is Regex Golf? An unstructured and informal programming competition... – More
This is quite an unusual post. It describes a for-fun application of a topic well-known in engineering and research: multiobjective optimization. We decided to blog about this anyway, because it may be of some interest for our students—and because it... – More