公开(公告)号：US20230325657A1

公开(公告)日：2023-10-12

申请号：US17972466

申请日：2022-10-24

申请人： Google LLC

发明人： Gregory S. Corrado ,  Kai Chen ,  Jeffrey A. Dean ,  Gary R. Holt ,  Julian P. Grady ,  Sharat Chikkerur ,  David W. Sculley, II

IPC分类号： G06N3/08 ,  G06N3/084 ,  G06F7/483 ,  G06F17/16 ,  G06N3/045 ,  G06N3/04

CPC分类号： G06N3/08 ,  G06N3/084 ,  G06F7/483 ,  G06F2207/483 ,  G06N3/045 ,  G06N3/04 ,  G06F17/16

摘要： 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.

公开(公告)号：US11954597B2

公开(公告)日：2024-04-09

申请号：US17972466

申请日：2022-10-24

申请人： Google LLC

发明人： Gregory S. Corrado ,  Kai Chen ,  Jeffrey A. Dean ,  Gary R. Holt ,  Julian P. Grady ,  Sharat Chikkerur ,  David W. Sculley, II

IPC分类号： G06N3/08 ,  G06F7/483 ,  G06F17/16 ,  G06N3/04 ,  G06N3/045 ,  G06N3/084

CPC分类号： G06N3/08 ,  G06F7/483 ,  G06F17/16 ,  G06N3/04 ,  G06N3/045 ,  G06N3/084 ,  G06F2207/483

摘要： 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.

公开(公告)号：US20240211759A1

公开(公告)日：2024-06-27

申请号：US18596535

申请日：2024-03-05

申请人： Google LLC

发明人： Gregory S. Corrado ,  Kai Chen ,  Jeffrey A. Dean ,  Gary R. Holt ,  Julian P. Grady ,  Sharat Chikkerur ,  David W. Sculley, II

IPC分类号： G06N3/08 ,  G06F7/483 ,  G06F17/16 ,  G06N3/04 ,  G06N3/045 ,  G06N3/084

CPC分类号： G06N3/08 ,  G06F7/483 ,  G06F17/16 ,  G06N3/04 ,  G06N3/045 ,  G06N3/084 ,  G06F2207/483

摘要： 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.

公开(公告)号：US10679124B1

公开(公告)日：2020-06-09

申请号：US15368460

申请日：2016-12-02

申请人： Google LLC

发明人： Gregory S. Corrado ,  Kai Chen ,  Jeffrey A. Dean ,  Gary R. Holt ,  Julian P. Grady ,  Sharat Chikkerur ,  David W. Sculley, II

IPC分类号： G06N3/08 ,  G06N3/04 ,  G06F7/483 ,  G06F17/16

摘要： 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.