9 citations · 18 across the 3 of their papers we have counts for
4 papers · 1 filter
Continual Learning from the Perspective of Compression
Xu He, Min Lin
Connectionist models such as neural networks suffer from catastrophic forgetting. In this work, we study this problem from the perspective of information theory and define forgetti…
Online Continual Learning with Maximally Interfered Retrieval
Rahaf Aljundi, Lucas Caccia, Eugene Belilovsky +4
Continual learning, the setting where a learning agent is faced with a never ending stream of data, continues to be a great challenge for modern machine learning systems. In partic…
Conditional Computation for Continual Learning
Min Lin, Jie Fu, Yoshua Bengio
Catastrophic forgetting of connectionist neural networks is caused by the global sharing of parameters among all training examples. In this study, we analyze parameter sharing unde…
Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud +1
A continual learning agent learns online with a non-stationary and never-ending stream of data. The key to such learning process is to overcome the catastrophic forgetting of previ…