公开(公告)号：US20230094479A1

公开(公告)日：2023-03-30

申请号：US17449660

申请日：2021-09-30

Applicant: Google LLC

Inventor： Xi Cheng ,  Lisa Yin ,  Mingge Deng ,  Amir Hormati ,  Umar Ali Syed ,  Jiashang Liu

IPC: G06N7/00 ,  G06K9/62

Abstract: A method includes receiving a model analysis request from a user. The model analysis requests requesting the data processing hardware to provide one or more statistics of a model trained on a dataset. The method also includes obtaining the trained model. The trained model includes a plurality of weights. Each weight is assigned to a feature of the trained model. The model also includes determining, using the dataset and the plurality of weights, the one or more statistics of the trained model based on a linear regression of the trained model. The method includes reporting the one or more statistics of the trained model to the user.

公开(公告)号：US20240221007A1

公开(公告)日：2024-07-04

申请号：US18605172

申请日：2024-03-14

Applicant: Google LLC

Inventor： Amir Hormati ,  Lisa Yin ,  Umar Ali Syed ,  Mingge Deng

IPC: G06Q30/0201 ,  G06F16/22 ,  G06F16/2453 ,  G06F17/16 ,  G06F18/214 ,  G06N5/04

CPC classification number: G06Q30/0201 ,  G06F16/221 ,  G06F16/24535 ,  G06F17/16 ,  G06F18/214 ,  G06N5/04

Abstract: A method includes obtaining a query to create a matrix factorization machine learning model based on a set of training data and determining a model vector and a data vector based on the set of training data. The method also includes determining a dot product between the model vector and the data vector, determining matrices based on the dot product, and generating item vectors using a linear solver based on the matrices. The method also includes generating the matrix factorization machine learning model based on the item vectors and executing the matrix factorization machine learning model.

公开(公告)号：US11948159B2

公开(公告)日：2024-04-02

申请号：US16843334

申请日：2020-04-08

Applicant: Google LLC

Inventor： Amir H. Hormati ,  Lisa Yin ,  Umar Ali Syed ,  Mingge Deng

IPC: G06F16/332 ,  G06F16/22 ,  G06F16/2453 ,  G06F17/16 ,  G06F18/214 ,  G06N5/04 ,  G06Q30/0201

CPC classification number: G06Q30/0201 ,  G06F16/221 ,  G06F16/24535 ,  G06F17/16 ,  G06F18/214 ,  G06N5/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scalable matrix factorization. A method includes obtaining a Structured Query Language (SQL) query to create a matrix factorization model based on a set of training data, generating SQL sub-queries that don't include non-scalable functions, obtaining the set of training data, and generating a matrix factorization model based on the set of training data and the SQL sub-queries that don't include non-scalable functions.

公开(公告)号：US20200320072A1

公开(公告)日：2020-10-08

申请号：US16843334

申请日：2020-04-08

Applicant: Google LLC

Inventor： Amir H. Hormati ,  Lisa Yin ,  Umar Ali Syed ,  Mingge Deng

IPC: G06F16/2453 ,  G06Q30/02 ,  G06F17/16 ,  G06F16/22 ,  G06K9/62 ,  G06N5/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scalable matrix factorization. A method includes obtaining a Structured Query Language (SQL) query to create a matrix factorization model based on a set of training data, generating SQL sub-queries that don't include non-scalable functions, obtaining the set of training data, and generating a matrix factorization model based on the set of training data and the SQL sub-queries that don't include non-scalable functions.