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Do you know which are the state-of-the-art approaches on this topic, and could you point me to some literature on them? This answer already mentions some of the approaches. More concretely, currently, the most common approaches to continual learning (i.e. learning with progressively more data while attempting to address the catastrophic forgetting problem) ...


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In general, is continuous learning possible with a deep convolutional neural network, without changing its topology? Your intuition that it is possible to perform incremental (aka continual, continuous or lifelong) learning by changing the NN's topology is correct. However, dynamically adapting the NN's topology is just one approach to continual learning (a ...


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There are lots of different approaches that try to avoid catastrophic forgetting in neural networks. It is impossible to summarize all contributions here. However, in addition to the already mentioned techniques, there are sparsity approaches that try to disentangle internal representations of the network on different tasks or learning steps. Sparsity ...


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