Invention Publication
- Patent Title: USING EMBEDDING FUNCTIONS WITH A DEEP NETWORK
-
Application No.: US18596535Application Date: 2024-03-05
-
Publication No.: US20240211759A1Publication Date: 2024-06-27
- Inventor: Gregory S. Corrado , Kai Chen , Jeffrey A. Dean , Gary R. Holt , Julian P. Grady , Sharat Chikkerur , David W. Sculley, II
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06F7/483 ; G06F17/16 ; G06N3/04 ; G06N3/045 ; G06N3/084

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using embedded function with a deep network. One of the methods includes receiving an input comprising a plurality of features, wherein each of the features is of a different feature type; processing each of the features using a respective embedding function to generate one or more numeric values, wherein each of the embedding functions operates independently of each other embedding function, and wherein each of the embedding functions is used for features of a respective feature type; processing the numeric values using a deep network to generate a first alternative representation of the input, wherein the deep network is a machine learning model composed of a plurality of levels of non-linear operations; and processing the first alternative representation of the input using a logistic regression classifier to predict a label for the input.
Information query