E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network. (arXiv:2207.06754v1 [cs.CV])

Expandable networks have demonstrated their advantages in dealing with
catastrophic forgetting problem in incremental learning. Considering that
different tasks may need different structures, recent methods design dynamic
structures adapted to different tasks via sophisticated skills. Their routine
is to search expandable structures first and then train on the new tasks,
which, however, breaks tasks into multiple training stages, leading to
suboptimal or overmuch computational cost. In this paper, we propose an
end-to-end trainable adaptively expandable network named E2-AEN, which
dynamically …

arxiv cv e2 incremental learning network