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- W2771011331 abstract "In the present work we propose a Deep Feed Forward network architecture which can be trained according to a sequential learning paradigm, where tasks of increasing difficulty are learned sequentially, yet avoiding catastrophic forgetting. The proposed architecture can re-use the features learned on previous tasks in a new task when the old tasks and the new one are related. The architecture needs fewer computational resources (neurons and connections) and less data for learning the new task than a network trained from scratch" @default.
- W2771011331 created "2017-12-04" @default.
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- W2771011331 date "2017-11-28" @default.
- W2771011331 modified "2023-09-25" @default.
- W2771011331 title "Block Neural Network Avoids Catastrophic Forgetting When Learning Multiple Task" @default.
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- W2771011331 hasPublicationYear "2017" @default.
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