Carlo Ciliberto

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Conditional Meta-Learning of Linear Representations.

[BibT_eX]

[DOI]

Giulia Denevi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Modular Adaptive Policy Selection for Multi- Task Imitation Learning through Task Division.

[BibT_eX]

[DOI]

Dafni Antotsiou

Tae-Kyun Kim

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Distribution Regression with Sliced Wasserstein Kernels.

[BibT_eX]

[DOI]

Dimitri Meunier

Proceedings of the International Conference on Machine Learning, 2022

Measuring dissimilarity with diffeomorphism invariance.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Structured Prediction for CRiSP Inverse Kinematics Learning With Misspecified Robot Models.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

The Role of Global Labels in Few-Shot Classification and How to Infer Them.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PSD Representations for Effective Probability Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Imitation Learning with Trajectorial Augmentation and Correction.

[BibT_eX]

[DOI]

Dafni Antotsiou

Tae-Kyun Kim

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020

Approximating Hamiltonian dynamics with the Nyström method.

[BibT_eX]

[DOI]

Quantum, 2020

A General Framework for Consistent Structured Prediction with Implicit Loss Embeddings.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2020

Generalization Properties of Optimal Transport GANs with Latent Distribution Learning.

[BibT_eX]

[DOI]

Giulia Luise

CoRR, 2020

Support-weighted Adversarial Imitation Learning.

[BibT_eX]

[DOI]

Pierluigi Vito Amadori

CoRR, 2020

A Structured Prediction Approach for Conditional Meta-Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Fast quantum learning with statistical guarantees.

[BibT_eX]

[DOI]

CoRR, 2020

Structured Prediction for Conditional Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Advantage of Conditional Meta-Learning for Biased Regularization and Fine Tuning.

[BibT_eX]

[DOI]

Giulia Denevi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Hyperbolic Manifold Regression.

[BibT_eX]

[DOI]

Gian Maria Marconi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Are we done with object recognition? The iCub robot's perspective.

[BibT_eX]

[DOI]

Robotics Auton. Syst., 2019

Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online-Within-Online Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Localized Structured Prediction.

[BibT_eX]

[DOI]

Francis R. Bach

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation.

[BibT_eX]

[DOI]

Pierluigi Vito Amadori

Proceedings of the 36th International Conference on Machine Learning, 2019

Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning-to-Learn Stochastic Gradient Descent with Biased Regularization.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Incremental Learning-to-Learn with Statistical Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Manifold Structured Prediction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differential Properties of Sinkhorn Approximation for Learning with Wasserstein Distance.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning To Learn Around A Common Mean.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Visual recognition for humanoid robots.

[BibT_eX]

[DOI]

Robotics Auton. Syst., 2017

Connecting YARP to the Web with Yarp.js.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2017

Reexamining Low Rank Matrix Factorization for Trace Norm Regularization.

[BibT_eX]

[DOI]

Dimitris Stamos

CoRR, 2017

Quantum machine learning: a classical perspective.

[BibT_eX]

[DOI]

Alessandro Davide Ialongo

Mark Herbster

CoRR, 2017

Consistent Multitask Learning with Nonlinear Output Relations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Incremental robot learning of new objects with fixed update time.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Low Compute and Fully Parallel Computer Vision with HashMatch.

[BibT_eX]

[DOI]

Sean Ryan Fanello

Julien P. C. Valentin

Proceedings of the IEEE International Conference on Computer Vision, 2017

2016

Enabling Depth-Driven Visual Attention on the iCub Humanoid Robot: Instructions for Use and New Perspectives.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2016

Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time.

[BibT_eX]

[DOI]

CoRR, 2016

A Consistent Regularization Approach for Structured Prediction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Object identification from few examples by improving the invariance of a Deep Convolutional Neural Network.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Active perception: Building objects' models using tactile exploration.

[BibT_eX]

[DOI]

Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

Combining sensory modalities and exploratory procedures to improve haptic object recognition in robotics.

[BibT_eX]

[DOI]

Proceedings of the 16th IEEE-RAS International Conference on Humanoid Robots, 2016

2015

Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn?

[BibT_eX]

[DOI]

CoRR, 2015

Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig.

[BibT_eX]

[DOI]

Comput. Intell. Neurosci., 2015

Teaching iCub to recognize objects using deep Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 4th Workshop on Machine Learning for Interactive Systems, 2015

Convex Learning of Multiple Tasks and their Structure.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Learning multiple visual tasks while discovering their structure.

[BibT_eX]

[DOI]