US Patent Issued to Maplebear on Nov. 3 for "Feature recommendations for machine learning models based on feature-model co-occurrences" (California, New Jersey Inventors)

ALEXANDRIA, Va., Nov. 3 -- United States Patent no. 12,783,943, issued on Nov. 3, was assigned to Maplebear Inc. (San Francisco).

"Feature recommendations for machine learning models based on feature-model co-occurrences" was invented by Guanghua Shu (Sunnyvale, Calif.), Reza Sadri (Irvine, Calif.), Jacob Jensen (Metuchen, N.J.) and Sahil Khanna (San Jose, Calif.).

According to the abstract* released by the U.S. Patent & Trademark Office: "A system maintains a data store for managing machine-learning (ML) models and features that are used by the models. The system generates a graph including nodes for each model and a node for each feature, and edges linking models and features that are used by the models. For a new model to be trained, t...