Papers › Automating Continual Learning

Automating Continual Learning

1 Dec 2023arXiv:2312.00276archive 2025-07-28

Kazuki Irie, Róbert Csordás, Jürgen Schmidhuber

General-purpose learning systems should improve themselves in open-ended fashion in ever-changing environments. Conventional learning algorithms for neural networks, however, suffer from catastrophic forgetting (CF) -- previously acquired skills are forgotten when a new task is learned. Instead of hand-crafting new algorithms for avoiding CF, we propose Automated Continual Learning (ACL) to train self-referential neural networks to meta-learn their own in-context continual (meta-)learning algorithms. ACL encodes all desiderata -- good performance on both old and new tasks -- into its meta-learning objectives. Our experiments demonstrate that ACL effectively solves "in-context catastrophic forgetting"; our ACL-learned algorithms outperform hand-crafted ones, e.g., on the Split-MNIST benchmark in the replay-free setting, and enables continual learning of diverse tasks consisting of multiple few-shot and standard image classification datasets.

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idsia/automated-cl officialmentioned in papermentioned on GitHubpytorchMIT report

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conv1x1 idsia/automated-cl/utils_other/resnet_impl.py official repository ran MIT (permissive) · de92832114f71d8c · report
conv3x3 idsia/automated-cl/utils_other/resnet_dropblock_impl.py official repository ran · our draft was wrong MIT (permissive) · fac5364e2f53c6db · report
conv3x3 idsia/automated-cl/utils_other/resnet_impl.py official repository ran MIT (permissive) · e5b7c79b0b62af96 · report
elu_p1 idsia/automated-cl/layer.py official repository ran · fixture could not drive it MIT (permissive) · fa08c36ab5558b55 · report
eval_model_one_shot idsia/automated-cl/utils_few_shot.py official repository ran MIT (permissive) · 1ca44a330df08f99 · report
eval_pretrain_model idsia/automated-cl/utils_few_shot.py official repository ran MIT (permissive) · 7a718af49bee3a35 · report
norm_layer idsia/automated-cl/utils_other/resnet_impl.py official repository ran MIT (permissive) · 319332ad3d5e39b1 · report
sum_norm idsia/automated-cl/layer.py official repository ran · fixture could not drive it MIT (permissive) · 379d7685e2a746e5 · report
eval_model idsia/automated-cl/utils_few_shot.py official repository unverified MIT (permissive) · 6c71a4a7bae9d5f3 · report
resnet12_dropblock idsia/automated-cl/utils_other/resnet_dropblock_impl.py official repository unverified MIT (permissive) · 2173141fe4baf439 · report

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Continual LearningImage ClassificationMeta-Learningimage-classification

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