Patent ID: 11972108
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for generating and using a basic state layer, said method comprising:
providing, by one or more processors of a computer system, N task models, wherein each task model is characterized by a unique task identifier (task ID) and was trained on a same pre-trained backbone model, wherein each task model comprises M feature layers and a task layer, wherein each feature layer m (m=1, . . . , M) of task model n (n=1, . . . , N) comprises parameter matrices Pnm that are different for the different models 1, . . . , N for each feature layer m due to each task model having been trained using different tasks, wherein N is at least 2 and M is at least 1;
training, by the one or more processors, an encoder-decoder model, wherein the encoder-decoder model comprises sequentially: an input layer, an encoder, M hidden layers, a decoder, and an output layer, wherein the input layer comprises the parameter matrices Pnm (n=1, . . . , N and m=1, . . . , M), wherein the encoder is a neural network that maps and compresses the parameter matrices in the input layer into the M hidden layers, wherein the M hidden layers with the mapped parameter matrices included therein are designated as the basic state model, and wherein the decoder is a neural network that receives the basic state model as input and generates the output layer to be identical to the input layer during said training; and
storing, by the one or more processors, the basic state model in a data storage repository.