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Continual Learning

285 평가 기록 62 datasets

Continual Learning (also known as Incremental Learning, Life-long Learning) is a concept to learn a model for a large number of tasks sequentially without forgetting knowledge obtained from the preceding tasks, where the data in the old tasks are not available anymore during training new ones.
If not mentioned, the benchmarks here are Task-CL, where task-id is provided on validation.

Source:
Continual Learning by Asymmetric Loss Approximation with Single-Side Overestimation
Three scenarios for continual learning
Lifelong Machine Learning
Continual lifelong learning with neural networks: A review

개요전체 데이터셋논문·평가 기록하위 태스크

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ASC (19 tasks)visual domain decathlon (10 tasks)PASCAL VOC 2012PASCAL VOC 2012PASCAL VOC 2012mini-ImagenetCIFAR-100Cifar100 (20 tasks)PASCAL VOC 2012PASCAL VOC 2012Tiny-ImageNet (10tasks)ADE20KPASCAL VOC 2012ADE20KADE20KF-CelebA (10 tasks)cifar10020Newsgroup (10 tasks)ADE20KCUB-200-2011CUBS (Fine-grained 6 Tasks)DSC (10 tasks)Flowers (Fine-grained 6 Tasks)ImageNet (Fine-grained 6 Tasks)Sketch (Fine-grained 6 Tasks)Stanford Cars (Fine-grained 6 Tasks)Wikiart (Fine-grained 6 Tasks)Cifar100 (10 tasks)ImageNet-50 (5 tasks)PASCAL VOC 2012
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