Incremental Learning Through Deep Adaptation

  title={Incremental Learning Through Deep Adaptation},
  author={Amir Rosenfeld and John K. Tsotsos},
Given an existing trained neural network, it is often desirable to be able to add new capabilities without hindering performance of already learned tasks. Existing approaches either learn sub-optimal solutions, require joint training, or incur a substantial increment in the number of parameters for each added task, typically as many as the original network. We propose a method which fully preserves performance on the original task, with only a small increase (around 20%) in the number of… CONTINUE READING
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