公开(公告)号：US20240119291A1

公开(公告)日：2024-04-11

申请号：US18203552

申请日：2023-05-30

Applicant: NVIDIA Corporation

Inventor： Jose M. Alvarez Lopez ,  Pavlo Molchanov ,  Hongxu Yin ,  Maying Shen ,  Lei Mao ,  Xinglong Sun

IPC: G06N3/082 ,  G06N3/0495

CPC classification number: G06N3/082 ,  G06N3/0495

Abstract: Machine learning is a process that learns a neural network model from a given dataset, where the model can then be used to make a prediction about new data. In order to reduce the size, computation, and latency of a neural network model, a compression technique can be employed which includes model sparsification. To avoid the negative consequences of pruning a fully pretrained neural network model and on the other hand of training a sparse model in the first place without any recovery option, the present disclosure provides a dynamic neural network model sparsification process which allows for recovery of previously pruned parts to improve the quality of the sparse neural network model.