3260 papers • 126 benchmarks • 313 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
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