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 | 740 | 2018 |
Forward and reverse gradient-based hyperparameter optimization L Franceschi, M Donini, P Frasconi, M Pontil International Conference on Machine Learning, 1165-1173, 2017 | 443 | 2017 |
Learning discrete structures for graph neural networks L Franceschi, M Niepert, M Pontil, X He International conference on machine learning, 1972-1982, 2019 | 420 | 2019 |
On the iteration complexity of hypergradient computation R Grazzi, L Franceschi, M Pontil, S Salzo International Conference on Machine Learning, 3748-3758, 2020 | 178 | 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 | 80 | 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 | 78 | 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 | 26* | 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 | 23 | 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 |
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 |
DAG learning on the permutahedron V Zantedeschi, L Franceschi, J Kaddour, MJ Kusner, V Niculae ICLR 2023, 2023 | 7 | 2023 |
Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models P Minervini, L Franceschi, M Niepert AAAI, 2022 | 6 | 2022 |
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 |
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 |
Explaining Probabilistic Models with Distributional Values L Franceschi, M Donini, C Archambeau, M Seeger arXiv preprint arXiv:2402.09947, 2024 | | 2024 |
Hands-on Tutorial:" Explanations in AI: Methods, Stakeholders and Pitfalls" MC Mayer, MB Zafar, L Franceschi, H Rangwala Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | | 2023 |