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ORCIDCarlo Ciliberto
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2020 – today
- 2024
[j9]Ruohan Wang
, John Isak Texas Falk, Massimiliano Pontil, Carlo Ciliberto:
Robust Meta-Representation Learning via Global Label Inference and Classification. IEEE Trans. Pattern Anal. Mach. Intell. 46(4): 1996-2010 (2024)- [i41]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Closed-form Filtering for Non-linear Systems. CoRR abs/2402.09796 (2024) - [i40]Pietro Novelli, Marco Pratticò, Massimiliano Pontil, Carlo Ciliberto:
Operator World Models for Reinforcement Learning. CoRR abs/2406.19861 (2024) - [i39]June Moh Goo, Xenios Milidonis, Alessandro Artusi, Jan Boehm, Carlo Ciliberto:
Hybrid-Segmentor: A Hybrid Approach to Automated Fine-Grained Crack Segmentation in Civil Infrastructure. CoRR abs/2409.02866 (2024) - 2022
- [c41]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Measuring dissimilarity with diffeomorphism invariance. ICML 2022: 2572-2596 - [c40]Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto:
Distribution Regression with Sliced Wasserstein Kernels. ICML 2022: 15501-15523 - [c39]Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim:
Modular Adaptive Policy Selection for Multi- Task Imitation Learning through Task Division. ICRA 2022: 2459-2465 - [c38]Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto:
Conditional Meta-Learning of Linear Representations. NeurIPS 2022 - [c37]Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil:
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces. NeurIPS 2022 - [c36]John Isak Texas Falk, Carlo Ciliberto, Massimiliano Pontil:
Implicit kernel meta-learning using kernel integral forms. UAI 2022: 652-662 - [i38]Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto:
Distribution Regression with Sliced Wasserstein Kernels. CoRR abs/2202.03926 (2022) - [i37]Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi:
Measuring dissimilarity with diffeomorphism invariance. CoRR abs/2202.05614 (2022) - [i36]Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim:
Modular Adaptive Policy Selection for Multi-Task Imitation Learning through Task Division. CoRR abs/2203.14855 (2022) - [i35]Vladimir Kostic, Pietro Novelli, Andreas Maurer, Carlo Ciliberto, Lorenzo Rosasco, Massimiliano Pontil:
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces. CoRR abs/2205.14027 (2022) - [i34]Ruohan Wang, Marco Ciccone, Giulia Luise, Andrew Yapp, Massimiliano Pontil, Carlo Ciliberto:
Schedule-Robust Online Continual Learning. CoRR abs/2210.05561 (2022) - [i33]Ruohan Wang, John Isak Texas Falk, Massimiliano Pontil, Carlo Ciliberto:
Robust Meta-Representation Learning via Global Label Inference and Classification. CoRR abs/2212.11702 (2022) - 2021
- [j8]Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco, Carlo Ciliberto:
Structured Prediction for CRiSP Inverse Kinematics Learning With Misspecified Robot Models. IEEE Robotics Autom. Lett. 6(3): 5650-5657 (2021) - [c35]Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim:
Adversarial Imitation Learning with Trajectorial Augmentation and Correction. ICRA 2021: 4724-4730 - [c34]Alessandro Rudi, Carlo Ciliberto:
PSD Representations for Effective Probability Models. NeurIPS 2021: 19411-19422 - [c33]Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto:
The Role of Global Labels in Few-Shot Classification and How to Infer Them. NeurIPS 2021: 27160-27170 - [i32]Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco, Carlo Ciliberto:
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models. CoRR abs/2102.12942 (2021) - [i31]Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim:
Adversarial Imitation Learning with Trajectorial Augmentation and Correction. CoRR abs/2103.13887 (2021) - [i30]Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto:
Conditional Meta-Learning of Linear Representations. CoRR abs/2103.16277 (2021) - [i29]Alessandro Rudi, Carlo Ciliberto:
PSD Representations for Effective Probability Models. CoRR abs/2106.16116 (2021) - [i28]Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto:
The Role of Global Labels in Few-Shot Classification and How to Infer Them. CoRR abs/2108.04055 (2021) - 2020
- [j7]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. J. Mach. Learn. Res. 21: 98:1-98:67 (2020) - [j6]Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini:
Approximating Hamiltonian dynamics with the Nyström method. Quantum 4: 234 (2020) - [c32]Gian Maria Marconi, Carlo Ciliberto, Lorenzo Rosasco:
Hyperbolic Manifold Regression. AISTATS 2020: 2570-2580 - [c31]Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto:
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine Tuning. NeurIPS 2020 - [c30]Luca Oneto, Michele Donini, Giulia Luise, Carlo Ciliberto, Andreas Maurer, Massimiliano Pontil:
Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning. NeurIPS 2020 - [c29]Ruohan Wang, Yiannis Demiris, Carlo Ciliberto:
Structured Prediction for Conditional Meta-Learning. NeurIPS 2020 - [i27]Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig:
Fast quantum learning with statistical guarantees. CoRR abs/2001.10477 (2020) - [i26]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. CoRR abs/2002.05424 (2020) - [i25]Ruohan Wang, Yiannis Demiris, Carlo Ciliberto:
A Structured Prediction Approach for Conditional Meta-Learning. CoRR abs/2002.08799 (2020) - [i24]Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris:
Support-weighted Adversarial Imitation Learning. CoRR abs/2002.08803 (2020) - [i23]Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto:
Hyperbolic Manifold Regression. CoRR abs/2005.13885 (2020) - [i22]Giulia Luise, Massimiliano Pontil, Carlo Ciliberto:
Generalization Properties of Optimal Transport GANs with Latent Distribution Learning. CoRR abs/2007.14641 (2020) - [i21]Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto:
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning. CoRR abs/2008.10857 (2020)
2010 – 2019
- 2019
- [j5]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Are we done with object recognition? The iCub robot's perspective. Robotics Auton. Syst. 112: 260-281 (2019) - [c28]Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil:
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization. ICML 2019: 1566-1575 - [c27]Giulia Luise, Dimitrios Stamos, Massimiliano Pontil, Carlo Ciliberto:
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction. ICML 2019: 4193-4202 - [c26]Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris:
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation. ICML 2019: 6536-6544 - [c25]Carlo Ciliberto, Francis R. Bach, Alessandro Rudi:
Localized Structured Prediction. NeurIPS 2019: 7299-7309 - [c24]Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto:
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. NeurIPS 2019: 9318-9329 - [c23]Giulia Denevi, Dimitris Stamos, Carlo Ciliberto, Massimiliano Pontil:
Online-Within-Online Meta-Learning. NeurIPS 2019: 13089-13099 - [i20]Giulia Luise, Dimitris Stamos, Massimiliano Pontil, Carlo Ciliberto:
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction. CoRR abs/1903.00667 (2019) - [i19]Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil:
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization. CoRR abs/1903.10399 (2019) - [i18]Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris:
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation. CoRR abs/1905.06750 (2019) - [i17]Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto:
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. CoRR abs/1905.13194 (2019) - 2018
- [c22]Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco:
Manifold Structured Prediction. NeurIPS 2018: 5615-5626 - [c21]Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto:
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. NeurIPS 2018: 5864-5874 - [c20]Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil:
Learning To Learn Around A Common Mean. NeurIPS 2018: 10190-10200 - [c19]Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil:
Incremental Learning-to-Learn with Statistical Guarantees. UAI 2018: 457-466 - [i16]Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil:
Incremental Learning-to-Learn with Statistical Guarantees. CoRR abs/1803.08089 (2018) - [i15]Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini:
Approximating Hamiltonian dynamics with the Nyström method. CoRR abs/1804.02484 (2018) - [i14]Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto:
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. CoRR abs/1805.11897 (2018) - [i13]Carlo Ciliberto, Francis R. Bach, Alessandro Rudi:
Localized Structured Prediction. CoRR abs/1806.02402 (2018) - [i12]Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco:
Manifold Structured Prediction. CoRR abs/1806.09908 (2018) - 2017
- [j4]Carlo Ciliberto:
Connecting YARP to the Web with Yarp.js. Frontiers Robotics AI 4: 67 (2017) - [j3]Sean Ryan Fanello, Carlo Ciliberto, Nicoletta Noceti, Giorgio Metta, Francesca Odone:
Visual recognition for humanoid robots. Robotics Auton. Syst. 91: 151-168 (2017) - [c18]Sean Ryan Fanello, Julien P. C. Valentin, Adarsh Kowdle, Christoph Rhemann, Vladimir Tankovich, Carlo Ciliberto, Philip Davidson, Shahram Izadi:
Low Compute and Fully Parallel Computer Vision with HashMatch. ICCV 2017: 3894-3903 - [c17]Raffaello Camoriano, Giulia Pasquale, Carlo Ciliberto, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta:
Incremental robot learning of new objects with fixed update time. ICRA 2017: 3207-3214 - [c16]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil:
Consistent Multitask Learning with Nonlinear Output Relations. NIPS 2017: 1986-1996 - [i11]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil:
Consistent Multitask Learning with Nonlinear Output Relations. CoRR abs/1705.08118 (2017) - [i10]Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil:
Reexamining Low Rank Matrix Factorization for Trace Norm Regularization. CoRR abs/1706.08934 (2017) - [i9]Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, Leonard Wossnig:
Quantum machine learning: a classical perspective. CoRR abs/1707.08561 (2017) - [i8]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Are we Done with Object Recognition? The iCub robot's Perspective. CoRR abs/1709.09882 (2017) - 2016
- [j2]Giulia Pasquale, Tanis Mar, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Enabling Depth-Driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives. Frontiers Robotics AI 3: 35 (2016) - [c15]Bertrand Higy, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics. Humanoids 2016: 117-124 - [c14]Nawid Jamali, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Active perception: Building objects' models using tactile exploration. Humanoids 2016: 179-185 - [c13]Giulia Pasquale, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network. IROS 2016: 4904-4911 - [c12]Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi:
A Consistent Regularization Approach for Structured Prediction. NIPS 2016: 4412-4420 - [i7]Raffaello Camoriano, Giulia Pasquale, Carlo Ciliberto, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta:
Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time. CoRR abs/1605.05045 (2016) - [i6]Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco:
A Consistent Regularization Approach for Structured Prediction. CoRR abs/1605.07588 (2016) - 2015
- [j1]Gian Luca Breschi, Carlo Ciliberto, Thierry Nieus, Lorenzo Rosasco, Stefano Taverna, Michela Chiappalone, Valentina Pasquale:
Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig. Comput. Intell. Neurosci. 2015: 359590:1-359590:11 (2015) - [c11]Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa:
Learning multiple visual tasks while discovering their structure. CVPR 2015: 131-139 - [c10]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Teaching iCub to recognize objects using deep Convolutional Neural Networks. MLIS@ICML 2015: 21-25 - [c9]Carlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco:
Convex Learning of Multiple Tasks and their Structure. ICML 2015: 1548-1557 - [i5]Carlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco:
Convex Learning of Multiple Tasks and their Structure. CoRR abs/1504.03101 (2015) - [i4]Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa:
Learning Multiple Visual Tasks while Discovering their Structure. CoRR abs/1504.03106 (2015) - [i3]Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale:
Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn? CoRR abs/1504.03154 (2015) - [i2]Giulia Pasquale, Tanis Mar, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale:
Enabling Depth-driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives. CoRR abs/1509.06939 (2015) - 2014
- [c8]Sean Ryan Fanello, Nicoletta Noceti, Carlo Ciliberto, Giorgio Metta, Francesca Odone:
Ask the Image: Supervised Pooling to Preserve Feature Locality. CVPR 2014: 851-858 - [c7]Carlo Ciliberto, Luca Fiorio, Marco Maggiali, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta, Giulio Sandini, Francesco Nori:
Exploiting global force torque measurements for local compliance estimation in tactile arrays. IROS 2014: 3994-3999 - 2013
- [c6]Sean Ryan Fanello, Carlo Ciliberto, Matteo Santoro, Lorenzo Natale, Giorgio Metta, Lorenzo Rosasco, Francesca Odone:
iCub World: Friendly Robots Help Building Good Vision Data-Sets. CVPR Workshops 2013: 700-705 - [c5]Sean Ryan Fanello, Carlo Ciliberto, Lorenzo Natale, Giorgio Metta:
Weakly supervised strategies for natural object recognition in robotics. ICRA 2013: 4223-4229 - [c4]Carlo Ciliberto, Sean Ryan Fanello, Matteo Santoro, Lorenzo Natale, Giorgio Metta, Lorenzo Rosasco:
On the impact of learning hierarchical representations for visual recognition in robotics. IROS 2013: 3759-3764 - [i1]Sean Ryan Fanello, Carlo Ciliberto, Matteo Santoro, Lorenzo Natale, Giorgio Metta, Lorenzo Rosasco, Francesca Odone:
iCub World: Friendly Robots Help Building Good Vision Data-Sets. CoRR abs/1306.3560 (2013) - 2012
- [c3]Carlo Ciliberto, Sean Ryan Fanello, Lorenzo Natale, Giorgio Metta:
A heteroscedastic approach to independent motion detection for actuated visual sensors. IROS 2012: 3907-3913 - 2011
- [c2]Carlo Ciliberto, Fabrizio Smeraldi, Lorenzo Natale, Giorgio Metta:
Online multiple instance learning applied to hand detection in a humanoid robot. IROS 2011: 1526-1532 - [c1]Carlo Ciliberto, Ugo Pattacini, Lorenzo Natale, Francesco Nori, Giorgio Metta:
Reexamining Lucas-Kanade method for real-time independent motion detection: Application to the iCub humanoid robot. IROS 2011: 4154-4160
Coauthor Index
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