| Bilevel programming for hyperparameter optimization and meta-learning L Franceschi, P Frasconi, S Salzo, R Grazzi, M Pontil International conference on machine learning, 1568-1577, 2018 | 794 | 2018 |
| Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International Conference on Machine Learning, 1165-1173, 2017 | 472 | 2017 |
| Learning discrete structures for graph neural networks L Franceschi, M Niepert, M Pontil, X He International conference on machine learning, 1972-1982, 2019 | 444 | 2019 |
| On the iteration complexity of hypergradient computation R Grazzi, L Franceschi, M Pontil, S Salzo International Conference on Machine Learning, 3748-3758, 2020 | 186 | 2020 |
| Fast and continuous foothold adaptation for dynamic locomotion through cnns OAV Magana, V Barasuol, M Camurri, L Franceschi, M Focchi, M Pontil, ... IEEE Robotics and Automation Letters 4 (2), 2140-2147, 2019 | 86 | 2019 |
| Implicit MLE: backpropagating through discrete exponential family distributions M Niepert, P Minervini, L Franceschi Advances in Neural Information Processing Systems 34, 14567-14579, 2021 | 85 | 2021 |
| MARTHE: Scheduling the Learning Rate Via Online Hypergradients M Donini, L Franceschi, O Majumder, M Pontil, P Frasconi Proceedings of the 29th International Joint Conference on Artificial …, 2020 | 28* | 2020 |
| Refactor gnns: Revisiting factorisation-based models from a message-passing perspective Y Chen, P Mishra, L Franceschi, P Minervini, PLE Saito Stenetorp, ... Advances in Neural Information Processing Systems 35, 16138-16150, 2022 | 25 | 2022 |
| A bridge between hyperparameter optimization and learning-to-learn L Franceschi, M Donini, P Frasconi, M Pontil arXiv preprint arXiv:1712.06283, 2017 | 18 | 2017 |
| DAG learning on the permutahedron V Zantedeschi, L Franceschi, J Kaddour, MJ Kusner, V Niculae ICLR 2023, 2023 | 9 | 2023 |
| Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models P Minervini, L Franceschi, M Niepert AAAI, 2022 | 9 | 2022 |
| A Speaker Adaptive DNN Training Approach for Speaker-independent Acoustic Inversion L Badino, L Franceschi, R Arora, M Donini, M Pontil Proc. Interspeech 2017, 984-988, 2017 | 8 | 2017 |
| A unified framework for gradient-based hyperparameter optimization and meta-learning L Franceschi UCL (University College London), 2021 | 5 | 2021 |
| On hyperparameter optimization in learning systems L Franceschi, M Donini, P Frasconi, M Pontil | 4 | 2017 |
| Far-HO: A bilevel programming package for hyperparameter optimization and meta-learning L Franceschi, R Grazzi, M Pontil, S Salzo, P Frasconi arXiv preprint arXiv:1806.04941, 2018 | 3 | 2018 |
| Explaining probabilistic models with distributional values L Franceschi, M Donini, C Archambeau, M Seeger ICML 2024 (Spotlight), 2024 | 1 | 2024 |
| Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography L Franceschi, C Zor, MB Zafar, G Detommaso, C Archambeau, T Madl, ... ICLR 2023 Workshop on Trustworthy Machine Learning for Healthcare, 2023 | 1 | 2023 |
| Learning Discrete Directed Acyclic Graphs via Backpropagation AJ Wren, P Minervini, L Franceschi, V Zantedeschi arXiv preprint arXiv:2210.15353, 2022 | 1 | 2022 |
| Graph structure learning for GCNs L Franceschi, M Niepert, M Pontil, X He A workshop paper at International Conference on Learning Representations (ICLR), 2019 | 1 | 2019 |
| Deep convolutional terrain assessment for visual reactive footstep correction on dynamic legged robots O Villarreal, V Barasuol, M Camurri, M Focchi, L Franceschi, M Pontil, ... IROS 2018 Workshop: Machine Learning in Robot Motion Planning, 2018 | 1 | 2018 |
Massimiliano PontilIstituto Italiano di Tecnologia & University College Londoniit.it의 이메일 확인됨
