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Politecnico di Milano
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Temporal performance drops? It's not always the model's fault: these new metrics disentangle adaptation from *inherent* data difficulty, revealing hidden patterns in how models handle evolving data.
Finally, a neural network that handles concept drift, temporal dependencies, and catastrophic forgetting in streaming time series, all at once.
Forget juggling CL and SML separately—Streaming Continual Learning (SCL) offers a single framework for rapid adaptation *and* knowledge retention in dynamic environments.
Forget incremental learning vs. streaming learning—a unified Streaming Continual Learning (SCL) framework promises faster adaptation without catastrophic forgetting in dynamic environments.