Carlo Ciliberto

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 73

Top Topics

Object Recognition

Structured Prediction

Norm Regularization

Reproducing Kernel

Top Venues

Publications

Pietro Novelli, Marco Pratticò, Massimiliano Pontil, Carlo Ciliberto
Operator World Models for Reinforcement Learning. CoRR (2024)
Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
Closed-form Filtering for Non-linear Systems. CoRR (2024)
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) (2024)
John Isak Texas Falk, Carlo Ciliberto, Massimiliano Pontil
Implicit kernel meta-learning using kernel integral forms. UAI (2022)
Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim
Modular Adaptive Policy Selection for Multi-Task Imitation Learning through Task Division. CoRR (2022)
Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
Measuring dissimilarity with diffeomorphism invariance. CoRR (2022)
Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj, Alessandro Rudi
Measuring dissimilarity with diffeomorphism invariance. ICML (2022)
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 (2022)
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)
Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
Conditional Meta-Learning of Linear Representations. NeurIPS (2022)
Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim
Modular Adaptive Policy Selection for Multi- Task Imitation Learning through Task Division. ICRA (2022)
Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto
Distribution Regression with Sliced Wasserstein Kernels. ICML (2022)
Ruohan Wang, John Isak Texas Falk, Massimiliano Pontil, Carlo Ciliberto
Robust Meta-Representation Learning via Global Label Inference and Classification. CoRR (2022)
Ruohan Wang, Marco Ciccone, Giulia Luise, Andrew Yapp, Massimiliano Pontil, Carlo Ciliberto
Schedule-Robust Online Continual Learning. CoRR (2022)
Dimitri Meunier, Massimiliano Pontil, Carlo Ciliberto
Distribution Regression with Sliced Wasserstein Kernels. CoRR (2022)
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) (2021)
Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto
The Role of Global Labels in Few-Shot Classification and How to Infer Them. CoRR (2021)
Alessandro Rudi, Carlo Ciliberto
PSD Representations for Effective Probability Models. NeurIPS (2021)
Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim
Adversarial Imitation Learning with Trajectorial Augmentation and Correction. ICRA (2021)
Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto
The Role of Global Labels in Few-Shot Classification and How to Infer Them. NeurIPS (2021)
Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim
Adversarial Imitation Learning with Trajectorial Augmentation and Correction. CoRR (2021)
Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
Conditional Meta-Learning of Linear Representations. CoRR (2021)
Alessandro Rudi, Carlo Ciliberto
PSD Representations for Effective Probability Models. CoRR (2021)
Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco, Carlo Ciliberto
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models. CoRR (2021)
Gian Maria Marconi, Carlo Ciliberto, Lorenzo Rosasco
Hyperbolic Manifold Regression. AISTATS (2020)
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)
Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. CoRR (2020)
Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning. CoRR (2020)
Ruohan Wang, Yiannis Demiris, Carlo Ciliberto
Structured Prediction for Conditional Meta-Learning. NeurIPS (2020)
Ruohan Wang, Yiannis Demiris, Carlo Ciliberto
A Structured Prediction Approach for Conditional Meta-Learning. CoRR (2020)
Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris
Support-weighted Adversarial Imitation Learning. CoRR (2020)
Giulia Luise, Massimiliano Pontil, Carlo Ciliberto
Generalization Properties of Optimal Transport GANs with Latent Distribution Learning. CoRR (2020)
Carlo Ciliberto, Andrea Rocchetto, Alessandro Rudi, Leonard Wossnig
Fast quantum learning with statistical guarantees. CoRR (2020)
Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini
Approximating Hamiltonian dynamics with the Nyström method. Quantum 4 (2020)
Gian Maria Marconi, Lorenzo Rosasco, Carlo Ciliberto
Hyperbolic Manifold Regression. CoRR (2020)
Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine Tuning. NeurIPS (2020)
Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings. J. Mach. Learn. Res. 21 (2020)
Giulia Luise, Dimitris Stamos, Massimiliano Pontil, Carlo Ciliberto
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction. CoRR (2019)
Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation. CoRR (2019)
Giulia Luise, Dimitrios Stamos, Massimiliano Pontil, Carlo Ciliberto
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction. ICML (2019)
Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization. ICML (2019)
Giulia Denevi, Dimitris Stamos, Carlo Ciliberto, Massimiliano Pontil
Online-Within-Online Meta-Learning. NeurIPS (2019)
Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. NeurIPS (2019)
Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, Yiannis Demiris
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation. ICML (2019)
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 (2019)
Giulia Denevi, Carlo Ciliberto, Riccardo Grazzi, Massimiliano Pontil
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization. CoRR (2019)
Carlo Ciliberto, Francis R. Bach, Alessandro Rudi
Localized Structured Prediction. NeurIPS (2019)
Giulia Luise, Saverio Salzo, Massimiliano Pontil, Carlo Ciliberto
Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm. CoRR (2019)
Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco
Manifold Structured Prediction. CoRR (2018)
Alessandro Rudi, Carlo Ciliberto, Gian Maria Marconi, Lorenzo Rosasco
Manifold Structured Prediction. NeurIPS (2018)
Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil
Incremental Learning-to-Learn with Statistical Guarantees. UAI (2018)
Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil
Learning To Learn Around A Common Mean. NeurIPS (2018)
Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. NeurIPS (2018)
Alessandro Rudi, Leonard Wossnig, Carlo Ciliberto, Andrea Rocchetto, Massimiliano Pontil, Simone Severini
Approximating Hamiltonian dynamics with the Nyström method. CoRR (2018)
Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil
Incremental Learning-to-Learn with Statistical Guarantees. CoRR (2018)
Giulia Luise, Alessandro Rudi, Massimiliano Pontil, Carlo Ciliberto
Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance. CoRR (2018)
Carlo Ciliberto, Francis R. Bach, Alessandro Rudi
Localized Structured Prediction. CoRR (2018)
Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil
Reexamining Low Rank Matrix Factorization for Trace Norm Regularization. CoRR (2017)
Raffaello Camoriano, Giulia Pasquale, Carlo Ciliberto, Lorenzo Natale, Lorenzo Rosasco, Giorgio Metta
Incremental robot learning of new objects with fixed update time. ICRA (2017)
Sean Ryan Fanello, Julien P. C. Valentin, Adarsh Kowdle, Christoph Rhemann, Vladimir Tankovich, Carlo Ciliberto, Philip L. Davidson, Shahram Izadi
Low Compute and Fully Parallel Computer Vision with HashMatch. ICCV (2017)
Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil
Consistent Multitask Learning with Nonlinear Output Relations. NIPS (2017)
Sean Ryan Fanello, Carlo Ciliberto, Nicoletta Noceti, Giorgio Metta, Francesca Odone
Visual recognition for humanoid robots. Robotics Auton. Syst. 91 (2017)
Carlo Ciliberto
Connecting YARP to the Web with Yarp.js. Frontiers Robotics AI 4 (2017)
Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale
Are we Done with Object Recognition? The iCub robot's Perspective. CoRR (2017)
Carlo Ciliberto, Mark Herbster, Alessandro Davide Ialongo, Massimiliano Pontil, Andrea Rocchetto, Simone Severini, Leonard Wossnig
Quantum machine learning: a classical perspective. CoRR (2017)
Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco, Massimiliano Pontil
Consistent Multitask Learning with Nonlinear Output Relations. CoRR (2017)
Carlo Ciliberto, Alessandro Rudi, Lorenzo Rosasco
A Consistent Regularization Approach for Structured Prediction. CoRR (2016)
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)
Bertrand Higy, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale
Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics. Humanoids (2016)
Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
A Consistent Regularization Approach for Structured Prediction. NIPS (2016)
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 (2016)
Nawid Jamali, Carlo Ciliberto, Lorenzo Rosasco, Lorenzo Natale
Active perception: Building objects' models using tactile exploration. Humanoids (2016)
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 (2016)
Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa
Learning Multiple Visual Tasks while Discovering their Structure. CoRR (2015)
Carlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco
Convex Learning of Multiple Tasks and their Structure. CoRR (2015)
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 (2015)
Carlo Ciliberto, Lorenzo Rosasco, Silvia Villa
Learning multiple visual tasks while discovering their structure. CVPR (2015)
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 (2015)
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 (2015)
Giulia Pasquale, Carlo Ciliberto, Francesca Odone, Lorenzo Rosasco, Lorenzo Natale
Teaching iCub to recognize objects using deep Convolutional Neural Networks. MLIS@ICML (2015)
Carlo Ciliberto, Youssef Mroueh, Tomaso A. Poggio, Lorenzo Rosasco
Convex Learning of Multiple Tasks and their Structure. ICML (2015)
Sean Ryan Fanello, Nicoletta Noceti, Carlo Ciliberto, Giorgio Metta, Francesca Odone
Ask the Image: Supervised Pooling to Preserve Feature Locality. CVPR (2014)
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)
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)
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)
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 (2013)
Sean Ryan Fanello, Carlo Ciliberto, Lorenzo Natale, Giorgio Metta
Weakly supervised strategies for natural object recognition in robotics. ICRA (2013)
Carlo Ciliberto, Sean Ryan Fanello, Lorenzo Natale, Giorgio Metta
A heteroscedastic approach to independent motion detection for actuated visual sensors. IROS (2012)
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)
Carlo Ciliberto, Fabrizio Smeraldi, Lorenzo Natale, Giorgio Metta
Online multiple instance learning applied to hand detection in a humanoid robot. IROS (2011)