Pengyu He

US Patent:

20230050538, Feb 16, 2023

Filed:

Mar 26, 2021

Appl. No.:

17/773650

Inventors:

- Mountain View CA, US
Pengyu He - Jersey City NJ, US

International Classification:

G06K 9/62
G06N 20/00

Abstract:

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for presenting a new machine learning model architecture. In some aspects, the methods include obtaining a training dataset with a plurality of training samples that includes feature variables and output variables. A first matrix is generated using the training dataset which is a sparse representation of the training dataset. Generating the first matrix can include generating a categorical representation of numeric features and an encoded representation of the categorical features. The methods further include generating a second, third and a fourth matrix. Each feature of the first matrix is then represented using a vector that includes a multiple adjustable parameters. The machine learning model can learn by adjusting values of the adjustable parameters using a combination of a loss function the fourth matrix, and the first matrix.