Class Incremental Learning
PulseAugur coverage of Class Incremental Learning — every cluster mentioning Class Incremental Learning across labs, papers, and developer communities, ranked by signal.
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New paper explains imbalanced forgetting in class-incremental learning
Researchers have identified a phenomenon called imbalanced forgetting in class-incremental learning, where some classes are forgotten more than others despite balanced rehearsal strategies. A new paper proposes three la…
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New classifier tackles class-incremental learning challenges
Researchers have developed a novel classifier called Hierarchical-Cluster SOINN (HC-SOINN) to improve Class-Incremental Learning (CIL). This new approach addresses the limitations of traditional Nearest Class Mean (NCM)…
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New SR2-LoRA method tackles catastrophic forgetting in AI models
Researchers have introduced SR$^2$-LoRA, a new method designed to combat catastrophic forgetting in class-incremental learning (CIL). The technique addresses the issue by focusing on the drift of inter-layer relations w…
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New method uses causal inference to improve class-incremental learning
Researchers have introduced a novel regularization method for Class Incremental Learning (CIL) that addresses catastrophic forgetting by focusing on causal sufficiency and necessity. This approach, termed CPNS, aims to …