Research topics

This research area addresses the development of machine learning techniques and systems for reasoning over complex domains involving multiple entities, relationships and constraints. The complexity of the information to be processed and of the tasks to be addressed calls for the design of elaborate architectures and advances in fields such as deep and statistical relational learning, structured prediction, multi-task learning, etc. Prototypical and main application domains are Computer Vision and Multimedia, Natural Language Processing, and Bioinformatics.
The Deep and Structured Machine Learning Research Program gathers the following research groups:

Faculty members

Antonio Longa
Massimiliano Mancini
Paolo Morettin
Andrea Passerini (coordinator)
Elisa Ricci
Paolo Rota
Nicu Sebe
Stefano Teso
Giovanna Paola Varni