Patents by Inventor Ou Jin

Ou Jin has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10602207
    Abstract: An online system receives content items from a third party content provider. For each content item, the online system inputs an image into a neural network and extracts a feature vector from a hidden layer of the neural network. The online system compresses each feature vector by assigning a label to each feature value representing whether the feature value was above a threshold value. The online system identifies a set of content items that the user has interacted with and determines a user feature vector by aggregating feature vectors of the set of content items. For a new set of content items, the online system compares the compressed feature vectors of the content item with the user feature vector. The online system selects one or more of the new content items based on the comparison and sends the selected content items to the user.
    Type: Grant
    Filed: August 3, 2018
    Date of Patent: March 24, 2020
    Assignee: Facebook, Inc.
    Inventors: Tianshi Gao, Xiangyu Wang, Ou Jin, Yifei Huang, Vignesh Ramanathan
  • Publication number: 20200045354
    Abstract: An online system receives content items from a third party content provider. For each content item, the online system inputs an image into a neural network and extracts a feature vector from a hidden layer of the neural network. The online system compresses each feature vector by assigning a label to each feature value representing whether the feature value was above a threshold value. The online system identifies a set of content items that the user has interacted with and determines a user feature vector by aggregating feature vectors of the set of content items. For a new set of content items, the online system compares the compressed feature vectors of the content item with the user feature vector. The online system selects one or more of the new content items based on the comparison and sends the selected content items to the user.
    Type: Application
    Filed: August 3, 2018
    Publication date: February 6, 2020
    Inventors: Tianshi Gao, Xiangyu Wang, Ou Jin, Yifei Huang, Vignesh Ramanathan
  • Publication number: 20190197190
    Abstract: In one embodiment, a method includes accessing a user profile associated with a user of an online social network, wherein the user profile identifies one or more topics that the user is interested in; accessing post vectors, wherein each post vector represents one of a plurality of posts, indicates one or more topics, and for each of the topics, indicates a probability that the post is related to the corresponding topic; ranking the posts based on comparisons between the user profile and the post vectors; and providing for display to the user posts based on the ranking.
    Type: Application
    Filed: December 27, 2017
    Publication date: June 27, 2019
    Inventors: Ying Zhang, Wenhai Yang, Ou Jin
  • Publication number: 20190197400
    Abstract: In one embodiment, a method includes accessing an input vector representing an input post, wherein the input post includes one or more n-grams and an image, the input vector corresponds to a point in a d-dimensional vector space, the input vector was generated by an artificial neural network (ANN) based on a text vector representing the one or more n-grams of the input post and an image vector representing the image of the input post; and the ANN was jointly trained to receive a text vector representing one or more n-grams of a post and an image vector representing an image of the post and then output a probability that the received post is related to the training posts of a training page; and determining a topic of the input post based on the input vector.
    Type: Application
    Filed: December 27, 2017
    Publication date: June 27, 2019
    Inventors: Ying Zhang, Wenhai Yang, Ou Jin
  • Publication number: 20190197399
    Abstract: In one embodiment, a method includes accessing an input vector representing an input post, wherein: the vector space comprises clusters each associated with a topic; each cluster was determined based on a clustering of training-page vectors corresponding to training pages that each comprise training posts, each training post submitted by a user to a training page and comprises content selected by the user; and each training-page vector was generated by an ANN that was trained, based on the training posts of training pages associated with the ANN, to receive a post and then output a probability that the received post is related to the training posts of the training pages; determining that the input vector is located within a particular cluster in the vector space; and determining a topic of the input post based on the topic associated with the particular cluster that the input vector is located within.
    Type: Application
    Filed: December 27, 2017
    Publication date: June 27, 2019
    Inventors: Ying Zhang, Wenhai Yang, Ou Jin
  • Patent number: 10229357
    Abstract: The present disclosure is directed to a high-capacity training and prediction machine learning platform that can support high-capacity parameter models (e.g., with 10 billion weights). The platform implements a generic feature transformation layer for joint updating and a distributed training framework utilizing shard servers to increase training speed for the high-capacity model size. The models generated by the platform can be utilized in conjunction with existing dense baseline models to predict compatibilities between different groupings of objects (e.g., a group of two objects, three objects, etc.).
    Type: Grant
    Filed: September 11, 2015
    Date of Patent: March 12, 2019
    Assignee: Facebook, Inc.
    Inventors: Ou Jin, Stuart Michael Bowers, Dmytro Dzhulgakov
  • Publication number: 20190073590
    Abstract: An optimized computer architecture for training an neural network includes a system having multiple GPUs. The neural network may be divided into separate portions, and a different portion is assigned to each of the multiple GPUs. Within each GPU, its portion is further divided across multiple training worker threads in multiple processing cores, and each processing core has lock-free access to a local parameter memory. The local parameter memory of each GPU is separately, and individually, synchronized with a remote master parameter memory by lock memory access. Each GPU has a separate set of communication worker threads dedicated to data transfer between the GPU and the remote parameter memory so that the GPU's training worker threads are not involved with cross GPU communications.
    Type: Application
    Filed: September 1, 2017
    Publication date: March 7, 2019
    Inventors: Qiang Wu, Ou Jin, Liang Xiong
  • Publication number: 20190005406
    Abstract: The present disclosure is directed to a high-capacity training and prediction machine learning platform that can support high-capacity parameter models (e.g., with 10 billion parameters). The platform generates a model for a metric of interest based on a known training set. The model includes parameters indicating importances of different features of the model, taken both singly and in pairs. The model may be applied to predict a value for the metric for given sets of objects, such as for a pair consisting of a user object and a content item object.
    Type: Application
    Filed: June 29, 2017
    Publication date: January 3, 2019
    Inventors: Andrey Malevich, Ou Jin
  • Publication number: 20180336490
    Abstract: To select the content to be presented to the user, a first latent vector is determined for a content item based on a first object associated with the content item. A second latent vector is determined for the content item based on a second object associated with the content item. A content item vector is then determined based on the first and second latent vectors. Furthermore, a user vector is determined based on interactions of the user with the first set of content objects and the second set of content objects. A score indicative of the likelihood of the user interacting with the content item is determined based on the content item vector and the user vector.
    Type: Application
    Filed: May 18, 2017
    Publication date: November 22, 2018
    Inventors: Tianshi Gao, Ahmad Abdulmageed Mohammed Abdulkader, Yifei Huang, Ou Jin, Liang Xiong
  • Patent number: 10002329
    Abstract: An online system simplifies modification of features used by machine learned models used by the online system, such as machined learned models with high dimensionality. The online system obtains a superset of features including features used by at least one machine learned model and may include additional features. From the superset of features, the online system generates various groups of features for a machine learned model. The groups of features may be a group including features currently used by the machine learned model, a group including all available features, and one or more intermediate groups. Intermediate groups include various numbers of features from the set selected based on measures of feature impact on the machine learned model associated with various features. A user may select a group of features, test the machine learning model using the selected group, and then launch the tested model based on the results.
    Type: Grant
    Filed: September 26, 2014
    Date of Patent: June 19, 2018
    Assignee: Facebook, Inc.
    Inventors: Hussein Mohamed Hassan Mehanna, Stuart Michael Bowers, Alexandre Defossez, Parv Oberoi, Ou Jin
  • Patent number: 9940359
    Abstract: Provided are techniques for a Data-Partitioned Secondary Index (DPSI) partition level join. While using a Data-Partitioned Secondary Index (DPSI) to perform a join of an outer table and an inner table, a different task from multiple tasks is assigned to each partition of the inner table. With each task, a join is performed of the outer table and the assigned partition of the inner table using the DPSI to generate results. The results from each different task are merged.
    Type: Grant
    Filed: May 23, 2014
    Date of Patent: April 10, 2018
    Assignee: International Business Machines Corporation
    Inventors: Brian L. Baggett, Michael A. Chang, Shuanglin Guo, Ou Jin, Terence P. Purcell
  • Publication number: 20170076198
    Abstract: The present disclosure is directed to a high-capacity training and prediction machine learning platform that can support high-capacity parameter models (e.g., with 10 billion weights). The platform implements a generic feature transformation layer for joint updating and a distributed training framework utilizing shard servers to increase training speed for the high-capacity model size. The models generated by the platform can be utilized in conjunction with existing dense baseline models to predict compatibilities between different groupings of objects (e.g., a group of two objects, three objects, etc.).
    Type: Application
    Filed: September 11, 2015
    Publication date: March 16, 2017
    Inventors: Ou Jin, Stuart Michael Bowers, Dmytro Dzhulgakov
  • Publication number: 20150339350
    Abstract: Provided are techniques for a Data-Partitioned Secondary Index (DPSI) partition level join. While using a Data-Partitioned Secondary Index (DPSI) to perform a join of an outer table and an inner table, a different task from multiple tasks is assigned to each partition of the inner table. With each task, a join is performed of the outer table and the assigned partition of the inner table using the DPSI to generate results. The results from each different task are merged.
    Type: Application
    Filed: May 23, 2014
    Publication date: November 26, 2015
    Applicant: International Business Machines Corporation
    Inventors: Brian L. Baggett, Michael A. Chang, Shuanglin Guo, Ou Jin, Terence P. Purcell
  • Publication number: 20150332310
    Abstract: An advertising system predicts advertisement reach for a received advertisement request based on an advertiser-specified bid amount and a specification of a target audience. The system samples the target audience, and for each sampled user of the target audience, accesses a recent impression history to obtain costs or bids associated with recent advertisement impressions. The system compares the advertiser-specified bid amount in the received advertisement request to costs or bid values associated with successful advertisement impressions, for each sampled user, in order to determine whether the received advertisement request would have won a bid auction for each given sampled user to successfully reach each given sampled user. An estimated aggregate reach for the sampled users is computed and extrapolated to the targeted user population to estimate a total reach of the advertisement content for the target audience.
    Type: Application
    Filed: May 15, 2014
    Publication date: November 19, 2015
    Applicant: Facebook, Inc.
    Inventors: Xinyi Cui, Wenjie Fu, Haomin Yu, Ou Jin, Eitan Shay, Richard Bill Sim, Jun Yang
  • Publication number: 20150332317
    Abstract: An advertising system receives from an advertiser at a social networking system an advertisement request, the advertisement request comprising advertisement content and a specification of a target audience for the advertisement content. The advertising system defines a plurality of bid values for the advertisement request. For each of the plurality of bid values, the advertisement system estimates a corresponding value of advertisement reach for the target audience, for example, by estimating a number of users of the target audience for each of whom the given bid value is expected to have resulted in at least one successful impression. The advertiser is provided a visual representation of a bid-reach landscape representing the estimated plurality of advertisement reach values as a function of the plurality of bid values. The advertising system provides, to the advertiser, one or more recommendations for bid values for which corresponding return-on-investment metrics exceed a specified threshold.
    Type: Application
    Filed: May 15, 2014
    Publication date: November 19, 2015
    Applicant: Facebook, Inc.
    Inventors: Xinyi Cui, Wenjie Fu, Haomin Yu, Ou Jin, Eitan Shay, Richard Bill Sim, Jun Yang
  • Patent number: 8140522
    Abstract: A database query is partitioned into an initial partition including a plurality of parallel groups, and is executed, via an execution plan, based on the initial partition. A sampling subset of data is identified from the plurality of parallel groups. Substantially in parallel with the executing of the query, the execution plan is executed on the sampling subset of data as a sampling thread. The execution plan is modified based on feedback from the execution of the execution plan on the sampling subset of data.
    Type: Grant
    Filed: August 12, 2008
    Date of Patent: March 20, 2012
    Assignee: International Business Machines Corporation
    Inventors: Hong Min, Yefim Shuf, Terence Patrick Purcell, You-Chin Fuh, Chunfeng Pei, Ou Jin
  • Patent number: 7930294
    Abstract: Techniques for partitioning a query are provided. The techniques include establishing one or more criterion for partitioning a query, wherein the query comprises one or more tables, materializing a first of the one or more tables, partitioning the first of the one or more tables until the one or more criterion have been satisfied, and partitioning and joining a remainder of the one or more tables of the query.
    Type: Grant
    Filed: August 12, 2008
    Date of Patent: April 19, 2011
    Assignee: International Business Machines Corporation
    Inventors: Yefim Shuf, Hong Min, Terence Patrick Purcell, Ou Jin, Fen-Ling Lin, Brian Thinh-Vinh Tran, Patrick Dooling Bossman
  • Patent number: 7877107
    Abstract: Disclosed is a method for transmitting a message during a PTT call service in a mobile communication terminal. The method includes checking whether a message transmission key is input during a PTT call service; when the message transmission key is input, displaying a screen containing a plurality of preset messages; when one message is selected, creating an SMS message using the selected message and transmitting the created SMS message to a pre-selected participant; and when a direct message creation is selected, receiving a selection of a participant to whom a message is to be transmitted, receiving an input message, creating an SMS message using the input message, and transmitting the created SMS message to the selected participant. Accordingly, even a participant having no right to speak can inform other participants of his or her own state.
    Type: Grant
    Filed: December 8, 2005
    Date of Patent: January 25, 2011
    Assignee: Samsung Electronics Co., Ltd
    Inventor: Ou-Jin Joung
  • Publication number: 20100042607
    Abstract: A database query is partitioned into an initial partition including a plurality of parallel groups, and is executed, via an execution plan, based on the initial partition. A sampling subset of data is identified from the plurality of parallel groups. Substantially in parallel with the executing of the query, the execution plan is executed on the sampling subset of data as a sampling thread. The execution plan is modified based on feedback from the execution of the execution plan on the sampling subset of data.
    Type: Application
    Filed: August 12, 2008
    Publication date: February 18, 2010
    Applicant: International Business Machines Corporation
    Inventors: Hong Min, Yefim Shuf, Terence Patrick Purcell, You-Chin Fuh, Chunfeng Pei, Ou Jin
  • Publication number: 20100042631
    Abstract: Techniques for partitioning a query are provided. The techniques include establishing one or more criterion for partitioning a query, wherein the query comprises one or more tables, materializing a first of the one or more tables, partitioning the first of the one or more tables until the one or more criterion have been satisfied, and partitioning and joining a remainder of the one or more tables of the query.
    Type: Application
    Filed: August 12, 2008
    Publication date: February 18, 2010
    Applicant: International Business Machines Corporation
    Inventors: Yefim Shuf, Hong Min, Terence Patrick Purcell, Ou Jin, Fen-Ling Lin, Brian Thinh-Vinh Tran, Patrick Dooling Bossman