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.
The Lab is part of DIA, University of Trieste, located in Trieste, Italy.

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Recent publications...

20-10-2015...not tightly related to our regex research. A short paper of ours has appeared today on an ACM Journal (a prestigious venue, as any other ACM venue): Data Quality Challenge: Toward a Tool for String Processing by Examples. The title should be quite...More

Source code for regex generator is now public

28-04-2015We have received several requests to make the source code for our regex generator by examples tool public. We were reluctant to do so because we cannot offer any support, but eventually we decided to make it public: Enjoy...More

Learning of Syntax Patterns: GECCO!

21-03-2015We have just received the acceptance notification of a work submitted to the most prestigious conference in evolutionary computation: ACM Genetic and Evolutionary Computation Conference (GECCO). We are proud to be there for the fourth year in row (2012,...More

Learning multiple patterns for text extraction

09-01-2015This new year has started very well. A paper describing one of the key improvements to our new regex generator tool has been just accepted at the prestigious 18-th European Conference on Genetic Programming (EuroGP)—despite its European qualification,...More

New regex generator tool online!

19-12-2014Our new regex generator is online! Let's summarize briefly what has happened. Epoch 1At ACM GECCO 2012 we presented a paper in which we described our work "Automatic generation of regular expressions from examples with genetic programming". We greatly...More