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Machine Learning
Machine Learning
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.
Publications
Publications
In our lab we focus on engineering applications: have a look at the list of our publications (or see here for an updated list).
People
People
The Lab is directed by prof. Alberto Bartoli, assisted by prof. Eric Medvet, prof. Andrea De Lorenzo and prof. Sylvio Barbon Junior, and hosts PostDocs, PhD students and LM, LT students: check the opportunities.
MOST Relevant Publications
MOST Relevant Publications
Full list here with abstract and pdf
Specializing Context-Free Grammars with a (1+1)-EA, IEEE Transactions on Evolutionary Computation, 2020
Genetic programming in the 21st century: a bibliometric and content-based analysis from both sides of the fence, Genetic Programming and Evolvable Machines, 2019
Enterprise Wi-Fi: we need devices that are secure by default, Communications of the ACM, 2019
Automatic Search-and-Replace from Examples with Coevolutionary Genetic Programming, IEEE Transactions on Cybernetics, 2019
On the Automatic Design of a Representation for Grammar-based Genetic Programming, 21st European Conference on Genetic Programming (EuroGP), 2018, Best paper
Evil Twins and WPA2 Enterprise: A Coming Security Disaster?, Computers & Security, 2018
Designing Automatically a Representation for Grammatical Evolution, Genetic Programming and Evolvable Machines
Weighted Hierarchical Grammatical Evolution, IEEE Transactions on Cybernetics, 2018
Unveiling Evolutionary Algorithm Representation with DU Maps, Genetic Programming and Evolvable Machines, 2018
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