Meta Platforms, Inc.

Yu Ning

Xin Liu

Peng Yang

Shyamsundar Rajaram

Robert Oliver Burns Zeldin

Jurgen Anne Francois Marie Van Gael

Hao Shi

Bingyue Peng

Piyush Bansal

Fei Xie

Zhen Yao

Machine-trained models are generated based on a model description that defines parameters for training the model and that can inherit parameters from parent model descriptions. When a parent model description changes, the changes made to the parent model description are applied to the model description automatically. When a target model is re-generated, a description of the set of parameters for generating the target model is received. The parent model is then identified from the received description, and a description of the set of parameters for generating the parent model is retrieved. Using the description for the target model and the parent model, a pipeline for generating the target model is generated. Finally, the pipeline is executed to generate the target model.

Automated generation of machine learning models

Growing community of inventors

Sunnyvale, CA, United States of America

Yu Ning