公开(公告)号：US20210029400A1

公开(公告)日：2021-01-28

申请号：US17071217

申请日：2020-10-15

Applicant: Google LLC

Inventor： Fong Shen ,  Tao Huang ,  Jian Chen ,  Yingwei Cui ,  Xiaodan Song

IPC: H04N21/2668 ,  H04N21/24 ,  H04N21/258 ,  H04N21/262 ,  H04N21/81 ,  H04N21/482

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content are disclosed. In one aspect, a method includes storing, in a data structure, data specifying a future live event. An opportunity to provide the specified content to a user at a user device is identified. It is determined that (i) a time of the opportunity is between a start time and an end time for the live event, (ii) that a user device is located in a same geographic region as the live event based on geographical data provided by the user device, and (iii) the user is interested in the live event based on attributes of the user matching attributes of other users that were identified as interested in the live event (e.g., based on evaluation of online search data). The content is provided for display at the user device.

公开(公告)号：US20220405579A1

公开(公告)日：2022-12-22

申请号：US17613773

申请日：2021-03-03

Applicant: Google LLC

Inventor： Jiahui Yu ,  Pengchong Jin ,  Hanxiao Liu ,  Gabriel Mintzer Bender ,  Pieter-Jan Kindermans ,  Mingxing Tan ,  Xiaodan Song ,  Ruoming Pang ,  Quoc V. Le

IPC: G06N3/08

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting a neural network to perform a particular machine learning task while satisfying a set of constraints.

公开(公告)号：US20220108221A1

公开(公告)日：2022-04-07

申请号：US17493442

申请日：2021-10-04

Applicant: Google LLC

Inventor： Dengyong Zhou ,  Xiaodan Song ,  Shuo Yang ,  Qiang Liu ,  Le Hou

IPC: G06N20/00

Abstract: Systems and methods of the present disclosure are directed to a computer-implemented method. The method can include obtaining a machine-learned model comprising a plurality of model units, wherein each model unit comprises a plurality of parameters that are tied to a shared plurality of parameters. The method can include performing a first plurality of training iterations with the machine-learned model to adjust parameters of the shared plurality of parameters. The method can include detecting, based on the first plurality of training iterations, an occurrence of an untying condition. The method can include untying the parameters of one or more model units from the shared plurality of parameters. The method can include performing a second plurality of training iterations with the machine-learned model to adjust parameters of the one or more model units independent of the shared plurality of parameters.

公开(公告)号：US11580170B2

公开(公告)日：2023-02-14

申请号：US16670809

申请日：2019-10-31

Applicant: Google LLC

Inventor： Xuerui Wang ,  Daniel Li ,  Xiaodan Song ,  Jie Han ,  Rahul Sharma

IPC: G06F16/906 ,  G06F16/215 ,  G06K9/62

Abstract: Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.

公开(公告)号：US11503355B2

公开(公告)日：2022-11-15

申请号：US17071217

申请日：2020-10-15

Applicant: Google LLC

Inventor： Fong Shen ,  Tao Huang ,  Jian Chen ,  Yingwei Cui ,  Xiaodan Song

IPC: H04N7/16 ,  H04N21/2668 ,  H04N21/24 ,  H04N21/258 ,  H04N21/262 ,  H04N21/81 ,  H04N21/482

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content are disclosed. In one aspect, a method includes storing, in a data structure, data specifying a future live event. An opportunity to provide the specified content to a user at a user device is identified. It is determined that (i) a time of the opportunity is between a start time and an end time for the live event, (ii) that a user device is located in a same geographic region as the live event based on geographical data provided by the user device, and (iii) the user is interested in the live event based on attributes of the user matching attributes of other users that were identified as interested in the live event (e.g., based on evaluation of online search data). The content is provided for display at the user device.

公开(公告)号：US10346492B2

公开(公告)日：2019-07-09

申请号：US15298324

申请日：2016-10-20

Applicant: Google LLC

Inventor： Bahman Rabii ,  Xiaodan Song ,  Yingwei Cui

IPC: G06F16/00 ,  G06F16/9535 ,  G06F16/9032 ,  G06F16/9038

Abstract: Systems and methods of providing information via a computer network are provided. A data processing system can identify a cluster that includes a plurality of online content items having a semantic or user similarity. The data processing system determines a plurality of cluster placement criteria of the cluster, and receives content configured for display with a web page. The content can be associated with the cluster based on the semantic or user similarity. A cluster placement criterion of the plurality of cluster placement criteria can be selected based on a quality metric of the selected cluster placement criterion, and the selected cluster placement criterion can be provided as a supplemental criterion used to select the content for display with the web page.

公开(公告)号：US12086211B2

公开(公告)日：2024-09-10

申请号：US18167297

申请日：2023-02-10

Applicant: Google LLC

Inventor： Xuerui Wang ,  Daniel Li ,  Xiaodan Song ,  Jie Han ,  Rahul Sharma

IPC: G06F18/23211 ,  G06F16/215 ,  G06F16/906 ,  G06F18/23213

CPC classification number: G06F18/23211 ,  G06F16/215 ,  G06F16/906 ,  G06F18/23213

Abstract: Generating granular clusters for real-time processing is provided. The systems can identify tokens based on aggregating input from computing devices over a time interval. The systems can identify, based on metrics, a subset of tokens for cluster generation. The systems can generate, via a clustering technique, token clusters from the subset of the tokens, each of the token clusters comprising two or more tokens from the subset of the tokens. The systems can apply a de-duplication technique to each of the token clusters. The systems can apply a filtering technique to the token clusters to remove tokens erroneously grouped in a token cluster. The systems can assign, based on a selection process, a label for each of the token clusters. The systems can activate, based on a number of remaining tokens in each of the token clusters, a subset of the token clusters for real-time content selection.

公开(公告)号：US20220108204A1

公开(公告)日：2022-04-07

申请号：US17061355

申请日：2020-10-01

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06N3/04 ,  G06F11/34

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.

公开(公告)号：US11036813B2

公开(公告)日：2021-06-15

申请号：US16145369

申请日：2018-09-28

Applicant: GOOGLE LLC

Inventor： Bahman Rabii ,  Xiaodan Song ,  Yingwei Cui

IPC: G06F16/00 ,  G06F16/9535 ,  G06F16/9032 ,  G06F16/9038

Abstract: Systems and methods of providing information via a computer network are provided. A data processing system can identify a cluster that includes a plurality of online content items having a semantic or user similarity. The data processing system determines a plurality of cluster placement criteria of the cluster, and receives content configured for display with a web page. The content can be associated with the cluster based on the semantic or user similarity. A cluster placement criterion of the plurality of cluster placement criteria can be selected based on a quality metric of the selected cluster placement criterion, and the selected cluster placement criterion can be provided as a supplemental criterion used to select the content for display with the web page.

公开(公告)号：US20240378509A1

公开(公告)日：2024-11-14

申请号：US18784068

申请日：2024-07-25

Applicant: Google LLC

Inventor： Xianzhi Du ,  Yin Cui ,  Tsung-Yi Lin ,  Quoc V. Le ,  Pengchong Jin ,  Mingxing Tan ,  Golnaz Ghiasi ,  Xiaodan Song

IPC: G06N20/00 ,  G06F11/34 ,  G06N3/04

Abstract: A computer-implemented method of generating scale-permuted models can generate models having improved accuracy and reduced evaluation computational requirements. The method can include defining, by a computing system including one or more computing devices, a search space including a plurality of candidate permutations of a plurality of candidate feature blocks, each of the plurality of candidate feature blocks having a respective scale. The method can include performing, by the computing system, a plurality of search iterations by a search algorithm to select a scale-permuted model from the search space, the scale-permuted model based at least in part on a candidate permutation of the plurality of candidate permutations.