A cloud-to-edge approach to support predictive analytics in robotics industry S Panicucci, N Nikolakis, T Cerquitelli, F Ventura, S Proto, E Macii, ... Electronics 9 (3), 492, 2020 | 49 | 2020 |
istep, an integrated self-tuning engine for predictive maintenance in industry 4.0 D Apiletti, C Barberis, T Cerquitelli, A Macii, E Macii, M Poncino, F Ventura 2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications …, 2018 | 43 | 2018 |
Expand your training limits! generating training data for ml-based data management F Ventura, Z Kaoudi, JA Quiané-Ruiz, V Markl Proceedings of the 2021 International Conference on Management of Data, 1865 …, 2021 | 29 | 2021 |
Discovering electricity consumption over time for residential consumers through cluster analysis T Cerquitelli, G Chicco, E Di Corso, F Ventura, G Montesano, A Del Pizzo, ... 2018 International Conference on Development and Application Systems (DAS …, 2018 | 28 | 2018 |
Self-tuning techniques for large scale cluster analysis on textual data collections E Di Corso, T Cerquitelli, F Ventura Proceedings of the Symposium on Applied Computing, 771-776, 2017 | 28 | 2017 |
PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes S Proto, F Ventura, D Apiletti, T Cerquitelli, E Baralis, E Macii, A Macii 2019 IEEE international congress on big data (bigDataCongress), 139-143, 2019 | 27 | 2019 |
Black-box model explained through an assessment of its interpretable features F Ventura, T Cerquitelli, F Giacalone New Trends in Databases and Information Systems: ADBIS 2018 Short Papers and …, 2018 | 24 | 2018 |
Towards a real-time unsupervised estimation of predictive model degradation T Cerquitelli, S Proto, F Ventura, D Apiletti, E Baralis Proceedings of real-time business intelligence and analytics, 1-6, 2019 | 21 | 2019 |
A new unsupervised predictive-model self-assessment approach that SCALEs F Ventura, S Proto, D Apiletti, T Cerquitelli, S Panicucci, E Baralis, E Macii, ... 2019 IEEE International Congress on Big Data (BigDataCongress), 144-148, 2019 | 20 | 2019 |
Enhancing manufacturing intelligence through an unsupervised data-driven methodology for cyclic industrial processes T Cerquitelli, F Ventura, D Apiletti, E Baralis, E Macii, M Poncino Expert Systems with Applications 182, 115269, 2021 | 19 | 2021 |
Clustering-based assessment of residential consumers from hourly-metered data T Cerquitelli, G Chicco, E Di Corso, F Ventura, G Montesano, M Armiento, ... 2018 International Conference on Smart Energy Systems and Technologies (SEST …, 2018 | 16 | 2018 |
Data miners' little helper: data transformation activity cues for cluster analysis on document collections T Cerquitelli, E Di Corso, F Ventura, S Chiusano Proceedings of the 7th International Conference on Web Intelligence, Mining …, 2017 | 16 | 2017 |
Trusting deep learning natural-language models via local and global explanations F Ventura, S Greco, D Apiletti, T Cerquitelli Knowledge and Information Systems 64 (7), 1863-1907, 2022 | 15 | 2022 |
Useful ToPIC: Self-tuning strategies to enhance latent Dirichlet allocation S Proto, E Di Corso, F Ventura, T Cerquitelli 2018 IEEE International Congress on Big Data (BigData Congress), 33-40, 2018 | 14 | 2018 |
All in a twitter: Self-tuning strategies for a deeper understanding of a crisis tweet collection E Di Corso, F Ventura, T Cerquitelli 2017 IEEE International Conference on Big Data (Big Data), 3722-3726, 2017 | 13 | 2017 |
Enabling predictive analytics for smart manufacturing through an IIoT platform T Cerquitelli, N Nikolakis, P Bethaz, S Panicucci, F Ventura, E Macii, ... IFAC-PapersOnLine 53 (3), 179-184, 2020 | 12 | 2020 |
What's in the box? Explaining the black-box model through an evaluation of its interpretable features F Ventura, T Cerquitelli arXiv preprint arXiv:1908.04348, 2019 | 10 | 2019 |
Automating concept-drift detection by self-evaluating predictive model degradation T Cerquitelli, S Proto, F Ventura, D Apiletti, E Baralis arXiv preprint arXiv:1907.08120, 2019 | 9 | 2019 |
DSLE: a smart platform for designing data science competitions G Attanasio, F Giobergia, A Pasini, F Ventura, E Baralis, L Cagliero, ... 2020 IEEE 44th Annual Computers, Software, and Applications Conference …, 2020 | 8 | 2020 |
Explaining the deep natural language processing by mining textual interpretable features F Ventura, S Greco, D Apiletti, T Cerquitelli arXiv preprint arXiv:2106.06697, 2021 | 7 | 2021 |