Overview
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 lab
The Machine Learning Lab is directed by prof. Alberto Bartoli, assisted by prof. Eric Medvet, and hosts PostDocs, PhD students and MS students: check the opportunities. Read also our blog to know more about lab life.
Recent news 
The Lab at ICWE 2012
16-04-2012 –
Our paper Recording and Replaying Navigations on AJAX Web Sites has
been accepted for presentation at the 2012 International Conference on
Web Engineering, which will be held in Berlin at the end of July.The
paper describes a tool we designed for registering... –
More
Two lab papers at i-Society 2012
27-03-2012 –
We will present the results of two our recent works at the IEEE
International Conference on Information Society (iSociety 2012), which
will held at the end of June in London.In the first work, titled A Tool
for Registering and Replaying Web Navigation,... –
More
Our work on GP for Regex at GECCO 2012
14-03-2012 –
Our paper Automatic Generation of Regular Expressions from Examples
with Genetic Programming has
been accepted at ACM Genetic and Evolutionary Computation Conference
(GECCO 2012).We propose a system based on genetic programming (GP) for
the automatic... –
More
Started large scale Twitter collection
20-01-2012 –
We just started a large scale collection of Twitter posts (aka tweets).
We are using a tool (TwitterSinkhole), written by our lab staff, which
collects about 40 tweets per second using the Twitter Streaming API.
This will result in about 3,500,000 tweets... –
More
PhD School at Krakow, Poland
17-01-2012 –
Two of our PhD students will attend the 3rd TMA PhD School in Krakow,
Poland.The program, titled "Traffic Understanding: From Traffic
Classification to Quality of Experience", will cover topics related to
traffic monitoring and machine learning. –
More
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