activity
20232025
collaborators

5 papers

cs.LG2025

Continual Learning Should Move Beyond Incremental Classification

Rupert Mitchell, Antonio Alliegro, Raffaello Camoriano +17

Continual learning (CL) is the sub-field of machine learning concerned with accumulating knowledge in dynamic environments. So far, CL research has mainly focused on incremental cl…

cs.CV2024

Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis

Andrea Maracani, Raffaello Camoriano, Elisa Maiettini +3

This study provides a comprehensive benchmark framework for Source-Free Unsupervised Domain Adaptation (SF-UDA) in image classification, aiming to achieve a rigorous empirical unde…

cs.RO2023

A Structured Prediction Approach for Robot Imitation Learning

Anqing Duan, Iason Batzianoulis, Raffaello Camoriano +3

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observe…

physics.optics2023

TempoRL: laser pulse temporal shape optimization with Deep Reinforcement Learning

Francesco Capuano, Davorin Peceli, Gabriele Tiboni +2

High Power Laser's (HPL) optimal performance is essential for the success of a wide variety of experimental tasks related to light-matter interactions. Traditionally, HPL parameter…

cs.LG2023

Key Design Choices for Double-Transfer in Source-Free Unsupervised Domain Adaptation

Andrea Maracani, Raffaello Camoriano, Elisa Maiettini +3

Fine-tuning and Domain Adaptation emerged as effective strategies for efficiently transferring deep learning models to new target tasks. However, target domain labels are not acces…