| Empirical risk minimization under fairness constraints M Donini, L Oneto, S Ben-David, JS Shawe-Taylor, M Pontil Advances in neural information processing systems 31, 2018 | 346 | 2018 |
| Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International Conference on Machine Learning, 1165-1173, 2017 | 276 | 2017 |
| EasyMKL: a scalable multiple kernel learning algorithm F Aiolli, M Donini Neurocomputing 169, 215-224, 2015 | 157 | 2015 |
| Taking advantage of multitask learning for fair classification L Oneto, M Doninini, A Elders, M Pontil Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 227-237, 2019 | 54 | 2019 |
| Fair bayesian optimization V Perrone, M Donini, MB Zafar, R Schmucker, K Kenthapadi, ... Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 854-863, 2021 | 43 | 2021 |
| General fair empirical risk minimization L Oneto, M Donini, M Pontil 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 36 | 2020 |
| Learning deep kernels in the space of dot product polynomials M Donini, F Aiolli Machine Learning 106, 1245-1269, 2017 | 31 | 2017 |
| Learning fair and transferable representations with theoretical guarantees L Oneto, M Donini, M Pontil, A Maurer 2020 IEEE 7th International Conference on Data Science and Advanced …, 2020 | 26 | 2020 |
| Stairstep recognition and counting in a serious Game for increasing users’ physical activity M Ciman, M Donini, O Gaggi, F Aiolli Personal and Ubiquitous Computing 20, 1015-1033, 2016 | 26 | 2016 |
| Multiple graph-kernel learning F Aiolli, M Donini, N Navarin, A Sperduti 2015 IEEE Symposium Series on Computational Intelligence, 1607-1614, 2015 | 23 | 2015 |
| Exploiting mmd and sinkhorn divergences for fair and transferable representation learning L Oneto, M Donini, G Luise, C Ciliberto, A Maurer, M Pontil Advances in Neural Information Processing Systems 33, 15360-15370, 2020 | 22 | 2020 |
| ClimbTheWorld: Real-time stairstep counting to increase physical activity F Aiolli, M Ciman, M Donini, O Gaggi Proceedings of the 11th International Conference on Mobile and Ubiquitous …, 2014 | 22 | 2014 |
| Amazon sagemaker automatic model tuning: Scalable gradient-free optimization V Perrone, H Shen, A Zolic, I Shcherbatyi, A Ahmed, T Bansal, M Donini, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 20* | 2021 |
| Scuba: scalable kernel-based gene prioritization G Zampieri, DV Tran, M Donini, N Navarin, F Aiolli, A Sperduti, G Valle BMC bioinformatics 19, 1-12, 2018 | 20 | 2018 |
| Voting with random classifiers (VORACE): theoretical and experimental analysis C Cornelio, M Donini, A Loreggia, MS Pini, F Rossi Autonomous Agents and Multi-Agent Systems 35 (2), 22, 2021 | 16 | 2021 |
| Amazon sagemaker clarify: Machine learning bias detection and explainability in the cloud M Hardt, X Chen, X Cheng, M Donini, J Gelman, S Gollaprolu, J He, ... arXiv preprint arXiv:2109.03285, 2021 | 16 | 2021 |
| Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important M Donini, JM Monteiro, M Pontil, T Hahn, AJ Fallgatter, J Shawe-Taylor, ... NeuroImage 195, 215-231, 2019 | 15 | 2019 |
| Multi-objective multi-fidelity hyperparameter optimization with application to fairness R Schmucker, M Donini, V Perrone, C Archambeau | 14 | 2020 |
| Measuring the expressivity of graph kernels through statistical learning theory L Oneto, N Navarin, M Donini, A Sperduti, F Aiolli, D Anguita Neurocomputing 268, 4-16, 2017 | 13 | 2017 |
| A multimodal multiple kernel learning approach to Alzheimer's disease detection M Donini, JM Monteiro, M Pontil, J Shawe-Taylor, J Mourao-Miranda 2016 IEEE 26th International Workshop on Machine Learning for Signal …, 2016 | 12 | 2016 |
Massimiliano PontilIstituto Italiano di Tecnologia & University College LondonBestätigte E-Mail-Adresse bei iit.it
