Tensor-Based Continual Learning Method and Apparatus

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Tensor-Based Continual Learning Method and Apparatus

This abstract first appeared for US patent application 18963964 titled 'Tensor-Based Continual Learning Method and Apparatus

Original Abstract Submitted

This application discloses a tensor-based continual learning method and apparatus. The method includes: obtaining input data; and inputting the input data into a first neural network to obtain a data processing result. After training of an itask ends, the neural network includes A tensor cores, the A tensor cores are divided into B tensor layers, and each of the B tensor layers includes data of all of the A tensor cores in a same dimension. In training of an (i+1)task, C tensor cores and/or D tensor layers are added to the first neural network, and parameters in the C tensor cores and/or parameters at the D tensor layers are updated. According to this application, an anti-forgetting capability of a model can be effectively improved, and an increase in a scale of the model is small, to effectively reduce storage and communication overheads.