Program
* Open Challenge Contribution
DAY 1, 28 November 2022
Welcome & Introduction (14.00 - 14.20)
Session 1: Theory
(14.20 - 14.40) Do we really need a new theory to understand the double-descent?
Luca Oneto, Sandro Ridella and Davide Anguita
(14.40 - 15.00) A relational view of feed-forward neural networks
Stefano Rovetta
(15.00 - 15.20) Weisfeiler–Lehman goes dynamic: an analysis of the expressive power of Graph Neural Networks for attributed and dynamic graphs
Silvia Beddar-Wiesing, Giuseppe Alessio D’Inverno, Caterina Graziani, Veronica Lachi, Alice Moallemy-Oureh, Franco Scarselli and Josephine Maria Thomas
Coffee Break (15.45 - 16.15)
Session 2: Machine Learning for Medicine
(16.15 - 16.35) Artificial intelligence forecasting algorithms for Type-I diabetic patients
Alessandro Marchetti, Federico D'Antoni and Mario Merone
(16.35 - 16.55) Explainable machine learning in medical imaging analysis *
Francesco Prinzi, Salvatore Vitabile and Salvatore Gaglio
(16.55 - 17.15) Automated PD-L1 scoring of whole slide images of breast cancer tumors
Giacomo Cignoni, Giuseppe Nicolò Fanelli, Cristian Scatena, Nicola Fusco, Antonio Giuseppe Naccarato and Alina Sîrbu
(17.15 - 17.35) Federated Survival Analysis *
Alberto Archetti and Matteo Matteucci
(17.35 - 17.55) AI and VR at the service of the inclusion of dislexic students in the university: the VRAIlexia project *
Andrea Zingoni, Juri Taborri and Giuseppe Calabrò
DAY 2, 29 November 2022
Welcome & Introduction (10.00 - 10.15)
Session 3: Deep Learning
(10.15 - 10.35) Injecting knowledge within neural learning architecture
Daniele Margiotta, Danilo Croce and Roberto Basili
Coffee Break (10.45 - 11.15)
(11.15 - 11.35) Visual Recommendation and Search through Deep Learning
Alessandro Abluton and Luigi Portinale
(11.35 - 11.55) Privacy-preserving deep learning with homomorphic encryption
Alessandro Falcetta, Davide Chiggiato and Manuel Roveri
(11.55 - 12.15) Topology preserving maps as aggregations for Graph Convolutional Neural Networks
Paolo Frazzetto, Luca Pasa, Nicolò Navarin and Alessandro Sperduti
(12.15 - 12.35) Machine learning techniques for inferring the museum visitors’ behavior
Alessio Ferrato, Carla Limongelli, Mauro Mezzini and Giuseppe Sansonetti
(12.35 - 12.55) Detecting and generating anomalies in semi-supervised settings
Angelica Liguori, Giuseppe Manco, Francesco Sergio Pisani, and Ettore Ritacco
Lunch Break (13.00 - 14.00)
Session 4: Miscellaneous
(15.00 - 15.20) Hybrid Quantum-classical computation for AI/ML *
Filippo Orazi, Antonio Macaluso, Stefano Lodi and Claudio Sartori
(15.20 - 15.40) Evaluating Choice models for simulating Users' interaction with Recommender Systems
Naieme Hazrati and Francesco Ricci
Coffee Break (15.45 - 16.15)
(16.15 - 16.35) Temporal network generation: a fast algorithm and some open problems
Antonio Longa, Giulia Cencetti, Sune Lehmann, Andrea Passerini and Bruno Lepri
Session 5: Probabilistic Learning
(16.35 - 16.55) Learning probabilistic logic constraints
Fabrizio Riguzzi, Elena Bellodi, Riccardo Zese, Marco Alberti and Evelina Lamma
(16.55 - 17.15) Intelligent tutoring systems by Bayesian nets with noisy gates
Alessandro Antonucci, Francesca Mangili, Claudio Bonesana and Giorgia Adorni
(17.15 - 17.35) On consistency of learning and inference in statistical relational learning
Sagar Malhotra and Luciano Serafini
(17.35 - 17.55) Semantic probabilistic layers for neuro-symbolic learning
Antonio Vergari