Parameter redundancy reduction method

Abstract

A method, computer program product, and computer system for generating and using a basic state layer. N task models are provided (N≥2). Each task model was trained on a same pre-trained backbone model. Each task model includes M feature layers and a task layer (M≥1). Each feature layer of each task model includes a parameter matrix that is different for the different models. An encoder-decoder model is trained. The encoder-decoder model includes sequentially: an input layer, an encoder, M hidden layers, a decoder, and an output layer. The encoder is a neural network that maps and compresses the parameter matrices in the input layer into the M hidden layers, which generates a basic state model. 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.