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Found 4 papers, 1 papers with code
Defying Imbalanced Forgetting in Class Incremental Learning
This intriguing phenomenon, discovered in replay-based Class Incremental Learning (CIL), highlights the imbalanced forgetting of learned classes, as their accuracy is similar before the occurrence of catastrophic forgetting.
Bilateral Memory Consolidation for Continual Learning
Humans are proficient at continuously acquiring and integrating new knowledge.
Exploring Domain Incremental Video Highlights Detection with the LiveFood Benchmark
However, most VHD methods are based on the closed world assumption, i. e., a fixed number of highlight categories is defined in advance and all training data are available beforehand.
Deep Encryption: Protecting Pre-Trained Neural Networks with Confusion Neurons
Having consumed huge amounts of training data and computational resource, large-scale pre-trained models are often considered key assets of AI service providers.
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