[Jun 28th 2018] LabMeeting: Learning with Architectural Constraints

Alessandro Betti (DIISM, Universities of Florence and Siena) Oct 4, 2018 – 9:30 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description By and large, Backpropagation (BP) is regarded as one of the most important neural computation algorithms at the basis of the progress in machine learning, including the recent advances in deep learning. […]

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Award cerimony

First Place at Hackathon Infinity

Three of our PhD students (Giuseppe Marra, Dario Zanca, and Andrea Zugarini, together with Giovanni Ciccone) won the Hackathon Mediaset Infinity, held in Rimini at Web Marketing Festival 2018. The goal of the challenge was to predict churn rate of users registered in infinitytv platform. Ten teams, composed of both students and professionals from Statistics […]

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[ Jun 21st 2018] Lab Meeting: Loss functions generation by means of fuzzy aggregators

Francesco Giannini (DIISM, University of Siena) Jun 21, 2018 – 9:30 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description In a learning from constraints problem, the prior knowledge can be expressed by logical formulas and then converted into real valued functions. Hence the satisfaction of a certain formula F can be enforced by […]

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[ Jun 14th 2018] Lab Meeting: A Character-Aware Neural Model to Learn Word and Context Representations

Andrea Zugarini (DIISM, University of Siena) Jun 14, 2018 – 9:30 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Word and context embeddings have been of significant help in achieving state-of-the-art results in different Natural Language Processing (NLP) tasks. The success of these representations comes from the learning process, tipycally accomplished in unsupervised […]

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[Jun 7th 2018] LabMeeting: Probabilistic Soft Logic

Giuseppe Marra (DIISM, University of Siena) Jun 7, 2018 – 9:30 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description A fundamental challenge in developing high-impact machine learning technologies is balancing the need to model rich, structured domains with the ability to scale to big data. Many important problem areas are both richly structured […]

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