45 citations · 168 across the 23 of their papers we have counts for
4 papers · 1 filter
The Role of Global Labels in Few-Shot Classification and How to Infer Them
Ruohan Wang, Massimiliano Pontil, Carlo Ciliberto
Few-shot learning is a central problem in meta-learning, where learners must quickly adapt to new tasks given limited training data. Recently, feature pre-training has become a ubi…
Conditional Meta-Learning of Linear Representations
Giulia Denevi, Massimiliano Pontil, Carlo Ciliberto
Standard meta-learning for representation learning aims to find a common representation to be shared across multiple tasks. The effectiveness of these methods is often limited when…
Structured Prediction for CRiSP Inverse Kinematics Learning with Misspecified Robot Models
Gian Maria Marconi, Raffaello Camoriano, Lorenzo Rosasco +1
With the recent advances in machine learning, problems that traditionally would require accurate modeling to be solved analytically can now be successfully approached with data-dri…
Adversarial Imitation Learning with Trajectorial Augmentation and Correction
Dafni Antotsiou, Carlo Ciliberto, Tae-Kyun Kim
Deep Imitation Learning requires a large number of expert demonstrations, which are not always easy to obtain, especially for complex tasks. A way to overcome this shortage of labe…