| Exercise levels and preferences in cancer patients: a cross-sectional study A Avancini, V Pala, I Trestini, D Tregnago, L Mariani, S Sieri, V Krogh, ... International journal of environmental research and public health 17 (15), 5351, 2020 | 91 | 2020 |
| Data of patients undergoing rehabilitation programs R Seccia, M Boresta, F Fusco, E Tronci, E Di Gemma, L Palagi, ... Data in brief 30, 105419, 2020 | 38 | 2020 |
| What drives a donor? A machine learning‐based approach for predicting responses of nonprofit direct marketing campaigns D Cacciarelli, M Boresta Journal of Philanthropy and Marketing 27 (2), e1724, 2022 | 15 | 2022 |
| A mixed finite differences scheme for gradient approximation M Boresta, T Colombo, A De Santis, S Lucidi Journal of Optimization Theory and Applications 194 (1), 1-24, 2022 | 5 | 2022 |
| Tuning parameters of deep neural network training algorithms pays off: a computational study C Coppola, L Papa, M Boresta, I Amerini, L Palagi TOP, 1-42, 2024 | 1 | 2024 |
| Managing low–acuity patients in an Emergency Department through simulation–based multiobjective optimization using a neural network metamodel M Boresta, T Giovannelli, M Roma Health Care Management Science, 1-21, 2024 | 1 | 2024 |
| Convolutional neural networks and multi-threshold analysis for contamination detection in the apparel industry M Boresta, T Colombo, A De Santis arXiv preprint arXiv:2207.12720, 2022 | 1 | 2022 |
| Optimal Network Design for Municipal Waste Management: Application to the Metropolitan City of Rome M Boresta, AL Croella, C Gentile, L Palagi, DM Pinto, G Stecca, P Ventura Logistics 8 (3), 79, 2024 | | 2024 |
| Bridging operations research and machine learning for service cost prediction in logistics and service industries M Boresta, DM Pinto, G Stecca Annals of Operations Research, 1-27, 2024 | | 2024 |
| Computational issues in Optimization for Deep networks C Coppola, L Papa, M Boresta, I Amerini, L Palagi arXiv preprint arXiv:2405.02089, 2024 | | 2024 |
| Enabling gradient-based optimization methods in problems with unreliable or absent derivatives M Boresta Università degli Studi di Roma" La Sapienza", 2022 | | 2022 |
| Customer Cost Forecasting Through Patterns Learning of Optimal Capacity Allocation DM Pinto, M Boresta, G Stecca Available at SSRN 4259923, 2022 | | 2022 |