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 at our publications.
The Lab is directed by prof. Alberto Bartoli, assisted by prof. Eric Medvet, and hosts PostDocs, PhD students and LM, LT students: check the opportunities.
Yet another great result for our multi-year activity on the automatic construction of regular expressions from examples of the desired behavior: our work "Active Learning of Regular Expressions for Entity Extraction" has been accepted for publication... – More
The lab has 1 one-year Postdoctoral fellowship available. The fellow will work on the "Design and development of a Machine Learning-based software system for detecting and predicting failures and wear in internal combustion engines", as part of a research... – More
Our work on automatic generation of regular expressions from examples (see this, this, this and this) has won the Silver Medal at the 2016 "Human competitive" awards (Humies). We are really very proud of this prestigious result. http://gecco-2016.sigevo.org/index.html/Humieshttp://human-competitive.org/ Humies... – More
Our work on automatic generation of regular expressions from examples (see this, this, this and this) has been selected for inclusion among the 8 finalists at the annual "HUMIES Awards for Human-Competitive Results produced by Genetic and Evolutionary... – More
Very good news for the lab: three papers just accepted at prestigious conferences! These papers focus on very different application domains and propose approaches based on very different machine learning paradigms. Syntactical Similarity Learning by means... – More