| Time and activity sequence prediction of business process instances M Polato, A Sperduti, A Burattin, M Leoni Computing 100, 1005-1031, 2018 | 196 | 2018 |
| LSTM networks for data-aware remaining time prediction of business process instances N Navarin, B Vincenzi, M Polato, A Sperduti 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2017 | 122 | 2017 |
| Data-aware remaining time prediction of business process instances M Polato, A Sperduti, A Burattin, M de Leoni 2014 International Joint Conference on Neural Networks (IJCNN), 816-823, 2014 | 122 | 2014 |
| A survey on hypergraph representation learning A Antelmi, G Cordasco, M Polato, V Scarano, C Spagnuolo, D Yang ACM Computing Surveys 56 (1), 1-38, 2023 | 50 | 2023 |
| Recency aware collaborative filtering for next basket recommendation G Faggioli, M Polato, F Aiolli Proceedings of the 28th ACM Conference on User Modeling, Adaptation and …, 2020 | 49 | 2020 |
| Mind your wallet's privacy: identifying bitcoin wallet apps and user's actions through network traffic analysis F Aiolli, M Conti, A Gangwal, M Polato Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 1484-1491, 2019 | 37 | 2019 |
| Model-free predictive current control for a SynRM drive based on an effective update of measured current responses D Da Rù, P Mirko, S Bolognani IEEE International Symposium on Predictive Control of Electrical Drives and …, 2017 | 31 | 2017 |
| Dissociation between users’ explicit and implicit attitudes toward artificial intelligence: An experimental study V Fietta, F Zecchinato, B Di Stasi, M Polato, M Monaro IEEE Transactions on Human-Machine Systems 52 (3), 481-489, 2021 | 29 | 2021 |
| Boolean kernels for collaborative filtering in top-N item recommendation M Polato, F Aiolli Neurocomputing 286, 214-225, 2018 | 26 | 2018 |
| Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation M Polato, F Aiolli Neurocomputing 268, 17-26, 2017 | 26 | 2017 |
| Radius-margin ratio optimization for dot-product boolean kernel learning I Lauriola, M Polato, F Aiolli Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017 | 21 | 2017 |
| Social support and help-seeking among suicide bereaved: a study with Italian survivors L Entilli, DD Leo, F Aiolli, M Polato, O Gaggi, S Cipolletta OMEGA-Journal of death and dying 87 (2), 534-553, 2023 | 19 | 2023 |
| Federated variational autoencoder for collaborative filtering M Polato 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 18 | 2021 |
| Dataset belonging to the help desk log of an Italian Company M Polato University of Padova, Padova 1, 2017 | 18 | 2017 |
| A preliminary study on a recommender system for the job recommendation challenge M Polato, F Aiolli Proceedings of the Recommender Systems Challenge 2016, 2016 | 18 | 2016 |
| Radical scavenging activity of natural antioxidants and drugs: Development of a combined machine learning and quantum chemistry protocol C Muraro, M Polato, M Bortoli, F Aiolli, L Orian The Journal of Chemical Physics 153 (11), 2020 | 17 | 2020 |
| Boosting the federation: Cross-silo federated learning without gradient descent M Polato, R Esposito, M Aldinucci 2022 International Joint Conference on Neural Networks (IJCNN), 1-10, 2022 | 15 | 2022 |
| Boolean kernels for rule based interpretation of support vector machines M Polato, F Aiolli Neurocomputing 342, 113-124, 2019 | 13 | 2019 |
| A novel boolean kernels family for categorical data M Polato, I Lauriola, F Aiolli Entropy 20 (6), 444, 2018 | 11 | 2018 |
| Kernel based collaborative filtering for very large scale top-n item recommendation M Polato, F Aiolli Proceedings of the European Symposium on Artificial Neural Networks …, 2016 | 11 | 2016 |
Fabio AiolliUniversity of Padova在 math.unipd.it 的电子邮件经过验证
