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Carlo Ciliberto
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Año
Quantum machine learning: a classical perspective
C Ciliberto, M Herbster, AD Ialongo, M Pontil, A Rocchetto, S Severini, ...
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018
5042018
Differential properties of sinkhorn approximation for learning with wasserstein distance
G Luise, A Rudi, M Pontil, C Ciliberto
Advances in Neural Information Processing Systems 31, 2018
1462018
Learning-to-learn stochastic gradient descent with biased regularization
G Denevi, C Ciliberto, R Grazzi, M Pontil
International Conference on Machine Learning, 1566-1575, 2019
1322019
Learning to learn around a common mean
G Denevi, C Ciliberto, D Stamos, M Pontil
Advances in neural information processing systems 31, 2018
1022018
Convex learning of multiple tasks and their structure
C Ciliberto, Y Mroueh, T Poggio, L Rosasco
International Conference on Machine Learning, 1548-1557, 2015
882015
A consistent regularization approach for structured prediction
C Ciliberto, L Rosasco, A Rudi
Advances in neural information processing systems 29, 2016
852016
Random expert distillation: Imitation learning via expert policy support estimation
R Wang, C Ciliberto, PV Amadori, Y Demiris
International Conference on Machine Learning, 6536-6544, 2019
762019
Sinkhorn barycenters with free support via frank-wolfe algorithm
G Luise, S Salzo, M Pontil, C Ciliberto
Advances in neural information processing systems 32, 2019
762019
Online-within-online meta-learning
G Denevi, D Stamos, C Ciliberto, M Pontil
Advances in Neural Information Processing Systems 32, 2019
732019
Object identification from few examples by improving the invariance of a deep convolutional neural network
G Pasquale, C Ciliberto, L Rosasco, L Natale
2016 IEEE/RSJ international conference on intelligent robots and systems …, 2016
672016
Active perception: Building objects' models using tactile exploration
N Jamali, C Ciliberto, L Rosasco, L Natale
2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids …, 2016
662016
Teaching iCub to recognize objects using deep Convolutional Neural Networks
G Pasquale, C Ciliberto, F Odone, L Rosasco, L Natale
Machine Learning for Interactive Systems, 21-25, 2015
662015
Learning dynamical systems via Koopman operator regression in reproducing kernel Hilbert spaces
V Kostic, P Novelli, A Maurer, C Ciliberto, L Rosasco, M Pontil
Advances in Neural Information Processing Systems 35, 4017-4031, 2022
602022
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
592020
Incremental learning-to-learn with statistical guarantees
G Denevi, C Ciliberto, D Stamos, M Pontil
arXiv preprint arXiv:1803.08089, 2018
552018
A general framework for consistent structured prediction with implicit loss embeddings
C Ciliberto, L Rosasco, A Rudi
Journal of Machine Learning Research 21 (98), 1-67, 2020
522020
Are we done with object recognition? The iCub robot’s perspective
G Pasquale, C Ciliberto, F Odone, L Rosasco, L Natale
Robotics and Autonomous Systems 112, 260-281, 2019
492019
Incremental robot learning of new objects with fixed update time
R Camoriano, G Pasquale, C Ciliberto, L Natale, L Rosasco, G Metta
2017 IEEE International Conference on Robotics and Automation (ICRA), 3207-3214, 2017
482017
The advantage of conditional meta-learning for biased regularization and fine tuning
G Denevi, M Pontil, C Ciliberto
Advances in Neural Information Processing Systems 33, 964-974, 2020
462020
Consistent multitask learning with nonlinear output relations
C Ciliberto, A Rudi, L Rosasco, M Pontil
Advances in Neural Information Processing Systems 30, 2017
382017
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