公开(公告)号：US20230244926A1

公开(公告)日：2023-08-03

申请号：US17592186

申请日：2022-02-03

Applicant: ADOBE INC.

Inventor： Sungchul Kim ,  Sejoon Oh ,  Ryan A. Rossi

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A data augmentation framework enhances the prediction accuracy of tensor completion methods. An array having a set of cells associated with a set of entities is received. Influence metrics of cells from the array are determined based on an influence of the cells on minimizing loss while training a machine learning model. An entity-importance metric is generated for each entity of the set of entities based on the influence metrics. A cell from the array for which to augment the array with a predicted value is identified. The cell is identified based on a sampling of the set of entities that is weighted by the entity-importance metric for each entity of the set of entities.