Publication

Found 8 results
Author Title Type [ Year(Desc)]
Filters: Author is Rosasco, Lorenzo  [Clear All Filters]
2022
Letizia, M. et al. Learning new physics efficiently with nonparametric methodsAbstract. The European Physical Journal C 82, (2022).
2023
Vega, C., Molinari, C., Rosasco, L. & Villa, S. Fast iterative regularization by reusing dataAbstract. Journal of Inverse and Ill-posed Problems (2023). doi:10.1515/jiip-2023-0009
Rangamani, A., Rosasco, L. & Poggio, T. For interpolating kernel machines, minimizing the norm of the ERM solution maximizes stability. Analysis and Applications 21, 193 - 215 (2023).
Villa, S., Matet, S., Vũ, B. Công & Rosasco, L. Implicit regularization with strongly convex bias: Stability and acceleration. Analysis and Applications 21, 165 - 191 (2023).
Lagomarsino-Oneto, D. et al. Physics informed machine learning for wind speed prediction. Energy 268, 126628 (2023).
Duan, A. et al. A structured prediction approach for robot imitation learning. The International Journal of Robotics Research 43, 113 - 133 (2023).
2024
Ceola, F., Rosasco, L., Natale, L. & Ceola, F. RESPRECT: Speeding-up Multi-Fingered Grasping With Residual Reinforcement LearningRESPRECT: Speeding-Up Multi-Fingered Grasping With Residual Reinforcement Learning_supp1-3363532.mp4. IEEE Robotics and Automation Letters 9, 3045 - 3052 (2024).
Alfano, P. Didier, Pastore, V. Paolo, Rosasco, L. & Odone, F. Top-tuning: A study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods. Image and Vision Computing 142, 104894 (2024).