12 citations · 14 across the 7 of their papers we have counts for
7 papers
MultiSTOP: Solving Functional Equations with Reinforcement Learning
Alessandro Trenta, Davide Bacciu, Andrea Cossu +1
We develop MultiSTOP, a Reinforcement Learning framework for solving functional equations in physics. This new methodology produces actual numerical solutions instead of bounds on…
Calibration of Continual Learning Models
Lanpei Li, Elia Piccoli, Andrea Cossu +2
Continual Learning (CL) focuses on maximizing the predictive performance of a model across a non-stationary stream of data. Unfortunately, CL models tend to forget previous knowled…
A Comprehensive Empirical Evaluation on Online Continual Learning
Albin Soutif--Cormerais, Antonio Carta, Andrea Cossu +4
Online continual learning aims to get closer to a live learning experience by learning directly on a stream of data with temporally shifting distribution and by storing a minimum a…
Projected Latent Distillation for Data-Agnostic Consolidation in Distributed Continual Learning
Antonio Carta, Andrea Cossu, Vincenzo Lomonaco +2
Distributed learning on the edge often comprises self-centered devices (SCD) which learn local tasks independently and are unwilling to contribute to the performance of other SDCs.…
Avalanche: A PyTorch Library for Deep Continual Learning
Antonio Carta, Lorenzo Pellegrini, Andrea Cossu +2
Continual learning is the problem of learning from a nonstationary stream of data, a fundamental issue for sustainable and efficient training of deep neural networks over time. Unf…
Continual Learning for Human State Monitoring
Federico Matteoni, Andrea Cossu, Claudio Gallicchio +2
Continual Learning (CL) on time series data represents a promising but under-studied avenue for real-world applications. We propose two new CL benchmarks for Human State Monitoring…