Patents by Inventor Tze Way Eugene Ie
Tze Way Eugene Ie 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).
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Publication number: 20240114158Abstract: A computer-implemented method for generating video representations utilizing a hierarchical video encoder includes obtaining a video, wherein the video includes a plurality of frames, processing each of the plurality of frames with a machine-learned frame-level encoder model to respectively generate a plurality of frame representations for the plurality of frames, the plurality of frame representations respective to the plurality of frames determining a plurality of segment representations representative of a plurality of video segments including one or more of the plurality of frames, the plurality of segment representations based at least in part on the plurality of frame representations, processing the plurality of segment representations with a machine-learned segment-level encoder model to generate a plurality of contextualized segment representations, determining a video representation based at least in part on the plurality of contextualized segment representations, and providing the video representatiType: ApplicationFiled: December 5, 2023Publication date: April 4, 2024Inventors: Vihan Jain, Joonseok Lee, Ming Zhao, Sheide Chammas, Hexiang Hu, Bowen Zhang, Fei Sha, Tze Way Eugene Ie
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Patent number: 11928133Abstract: Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.Type: GrantFiled: August 23, 2021Date of Patent: March 12, 2024Assignee: Pinterest, Inc.Inventors: Ningning Hu, Tze Way Eugene Ie
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Publication number: 20240047010Abstract: A method is provided for determining a sample genome from a plurality of read fragments and a reference genome. The method includes: (i) applying a first putative variant event, selected from a set of candidate variant events, to the sample genome to update the sample genome; (ii) mapping the plurality of read fragments to the updated sample genome; (hi) based on the mapping of the plurality of read fragments to the updated sample genome, determining a first read mapping cost function; and (iv) based on the first read mapping cost function, retaining the updated sample genome and removing the first putative variant event from the set of candidate variant events.Type: ApplicationFiled: February 1, 2022Publication date: February 8, 2024Inventors: Ali BASHIR, Zahra SHAMSI, Wesley Wei QIAN, Tze Way Eugene IE, Jeffrey CHAN, Marc BERNDL, Martin MLADENOV, Lawrence Stephen LANSING
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Patent number: 11876986Abstract: A computer-implemented method for generating video representations utilizing a hierarchical video encoder includes obtaining a video, wherein the video includes a plurality of frames, processing each of the plurality of frames with a machine-learned frame-level encoder model to respectively generate a plurality of frame representations for the plurality of frames, the plurality of frame representations respective to the plurality of frames determining a plurality of segment representations representative of a plurality of video segments including one or more of the plurality of frames, the plurality of segment representations based at least in part on the plurality of frame representations, processing the plurality of segment representations with a machine-learned segment-level encoder model to generate a plurality of contextualized segment representations, determining a video representation based at least in part on the plurality of contextualized segment representations, and providing the video representatiType: GrantFiled: November 29, 2022Date of Patent: January 16, 2024Assignee: GOOGLE LLCInventors: Vihan Jain, Joonseok Lee, Ming Zhao, Sheide Chammas, Hexiang Hu, Bowen Zhang, Fei Sha, Tze Way Eugene Ie
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Patent number: 11663520Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training machine learning systems. One of the methods includes receiving a plurality of training examples; and training a machine learning system on each of the plurality of training examples to determine trained values for weights of a machine learning model, wherein training the machine learning system comprises: assigning an initial value for a regularization penalty for a particular weight for a particular feature; and adjusting the initial value for the regularization penalty for the particular weight for the particular feature during the training of the machine learning system.Type: GrantFiled: August 26, 2019Date of Patent: May 30, 2023Assignee: Google LLCInventors: Yoram Singer, Tal Shaked, Tushar Deepak Chandra, Tze Way Eugene Ie
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Patent number: 11652866Abstract: Described are systems and methods for establishing and generating collections of sets that contain object identifiers based on user provided annotations for the object identifiers. A set may include one or more object identifiers and each object identifier may include one or more user provided annotations. Annotations from all object identifiers within a set are processed to form a set profile signature representative of the set. The set profile signatures are then compared between different sets to identify similar sets. Similar sets are included in a collection. Utilizing set profile signatures for a set formed based on user provided annotations provides useful relationships between sets that might otherwise not exist.Type: GrantFiled: January 10, 2022Date of Patent: May 16, 2023Assignee: Pinterest, Inc.Inventor: Tze Way Eugene Ie
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Publication number: 20230117499Abstract: A computing system for simulating allocation of resources to a plurality of entities is disclosed. The computing system can be configured to input an entity profile that describes a preference and/or demand of a simulated entity into a reinforcement learning agent model and receive, as an output of the reinforcement learning agent model, an allocation output that describes a resource allocation for the simulated entity. The computing system can select one or more resources based on the resource allocation described by the allocation output and provide the resource(s) to an entity model that is configured to simulate a simulated response output that describes a response of the simulated entity. The computing system can receive, as an output of the entity model, the simulated response output and update a resource profile that describes the at least one resource and/or the entity profile based on the simulated response output.Type: ApplicationFiled: October 17, 2022Publication date: April 20, 2023Inventors: Tze Way Eugene Ie, Sanmit Santosh Narvekar, Craig Edgar Boutilier
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Publication number: 20230103148Abstract: A computer-implemented method for generating video representations utilizing a hierarchical video encoder includes obtaining a video, wherein the video includes a plurality of frames, processing each of the plurality of frames with a machine-learned frame-level encoder model to respectively generate a plurality of frame representations for the plurality of frames, the plurality of frame representations respective to the plurality of frames determining a plurality of segment representations representative of a plurality of video segments including one or more of the plurality of frames, the plurality of segment representations based at least in part on the plurality of frame representations, processing the plurality of segment representations with a machine-learned segment-level encoder model to generate a plurality of contextualized segment representations, determining a video representation based at least in part on the plurality of contextualized segment representations, and providing the video representatiType: ApplicationFiled: November 29, 2022Publication date: March 30, 2023Inventors: Vihan Jain, Joonseok Lee, Ming Zhao, Sheide Chammas, Hexiang Hu, Bowen Zhang, Fei Sha, Tze Way Eugene Ie
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Patent number: 11533495Abstract: A computer-implemented method for generating video representations utilizing a hierarchical video encoder includes obtaining a video, wherein the video includes a plurality of frames, processing each of the plurality of frames with a machine-learned frame-level encoder model to respectively generate a plurality of frame representations for the plurality of frames, the plurality of frame representations respective to the plurality of frames determining a plurality of segment representations representative of a plurality of video segments including one or more of the plurality of frames, the plurality of segment representations based at least in part on the plurality of frame representations, processing the plurality of segment representations with a machine-learned segment-level encoder model to generate a plurality of contextualized segment representations, determining a video representation based at least in part on the plurality of contextualized segment representations, and providing the video representatiType: GrantFiled: January 29, 2021Date of Patent: December 20, 2022Assignee: GOOGLE LLCInventors: Vihan Jain, Joonseok Lee, Ming Zhao, Sheide Chammas, Hexiang Hu, Bowen Zhang, Fei Sha, Tze Way Eugene Ie
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Patent number: 11475355Abstract: A computing system for simulating allocation of resources to a plurality of entities is disclosed. The computing system can be configured to input an entity profile that describes a preference and/or demand of a simulated entity into a reinforcement learning agent model and receive, as an output of the reinforcement learning agent model, an allocation output that describes a resource allocation for the simulated entity. The computing system can select one or more resources based on the resource allocation described by the allocation output and provide the resource(s) to an entity model that is configured to simulate a simulated response output that describes a response of the simulated entity. The computing system can receive, as an output of the entity model, the simulated response output and update a resource profile that describes the at least one resource and/or the entity profile based on the simulated response output.Type: GrantFiled: February 28, 2019Date of Patent: October 18, 2022Assignee: GOOGLE LLCInventors: Tze Way Eugene Ie, Sanmit Santosh Narvekar, Craig Edgar Boutilier
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Publication number: 20220256175Abstract: A computer-implemented method for generating video representations utilizing a hierarchical video encoder includes obtaining a video, wherein the video includes a plurality of frames, processing each of the plurality of frames with a machine-learned frame-level encoder model to respectively generate a plurality of frame representations for the plurality of frames, the plurality of frame representations respective to the plurality of frames determining a plurality of segment representations representative of a plurality of video segments including one or more of the plurality of frames, the plurality of segment representations based at least in part on the plurality of frame representations, processing the plurality of segment representations with a machine-learned segment-level encoder model to generate a plurality of contextualized segment representations, determining a video representation based at least in part on the plurality of contextualized segment representations, and providing the video representatiType: ApplicationFiled: January 29, 2021Publication date: August 11, 2022Inventors: Vihan Jain, Joonseok Lee, Ming Zhao, Sheide Chammas, Hexiang Hu, Bowen Zhang, Fei Sha, Tze Way Eugene Ie
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Publication number: 20220131924Abstract: Described are systems and methods for establishing and generating collections of sets that contain object identifiers based on user provided annotations for the object identifiers. A set may include one or more object identifiers and each object identifier may include one or more user provided annotations. Annotations from all object identifiers within a set are processed to form a set profile signature representative of the set. The set profile signatures are then compared between different sets to identify similar sets. Similar sets are included in a collection. Utilizing set profile signatures for a set formed based on user provided annotations provides useful relationships between sets that might otherwise not exist.Type: ApplicationFiled: January 10, 2022Publication date: April 28, 2022Inventor: Tze Way Eugene Ie
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Publication number: 20220043837Abstract: Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.Type: ApplicationFiled: August 23, 2021Publication date: February 10, 2022Inventors: Ningning Hu, Tze Way Eugene Ie
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Patent number: 11228633Abstract: Described are systems and methods for establishing and generating collections of sets that contain object identifiers based on user provided annotations for the object identifiers. A set may include one or more object identifiers and each object identifier may include one or more user provided annotations. Annotations from all object identifiers within a set are processed to form a set profile signature representative of the set. The set profile signatures are then compared between different sets to identify similar sets. Similar sets are included in a collection. Utilizing set profile signatures for a set formed based on user provided annotations provides useful relationships between sets that might otherwise not exist.Type: GrantFiled: November 6, 2020Date of Patent: January 18, 2022Assignee: Pinterest, Inc.Inventor: Tze Way Eugene Ie
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Patent number: 11106700Abstract: Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.Type: GrantFiled: October 17, 2018Date of Patent: August 31, 2021Assignee: Pinterest, Inc.Inventors: Ningning Hu, Tze Way Eugene Ie
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Publication number: 20210081753Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reinforcement learning in combinatorial action spaces. One of the methods includes receiving an observation characterizing a current state of an environment; for each of a plurality of candidate actions: processing a network input using a Q neural network to generate a Q value that represents a return received if the candidate action is selected while the candidate action is presented in response to the received observation, processing the network input using a myopic neural network to generate a myopic output that represents a likelihood that the candidate action will be selected if the candidate action is presented in response to the received observation, and combining the myopic output and the Q value for the candidate action to generate a selection score for the candidate action; and selecting the candidate actions having the highest selection scores.Type: ApplicationFiled: May 20, 2019Publication date: March 18, 2021Applicant: Google LLCInventors: Tze Way Eugene IE, Vihan JAIN, Jing WANG, Ritesh AGARWAL, Craig Edgar BOUTILIER
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Patent number: 10833970Abstract: Described are systems and methods for establishing and generating collections of sets that contain object identifiers based on user provided annotations for the object identifiers. A set may include one or more object identifiers and each object identifier may include one or more user provided annotations. Annotations from all object identifiers within a set are processed to form a set profile signature representative of the set. The set profile signatures are then compared between different sets to identify similar sets. Similar sets are included in a collection. Utilizing set profile signatures for a set formed based on user provided annotations provides useful relationships between sets that might otherwise not exist.Type: GrantFiled: March 20, 2019Date of Patent: November 10, 2020Assignee: Pinterest, Inc.Inventor: Tze Way Eugene Ie
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Publication number: 20200250575Abstract: A computing system for simulating allocation of resources to a plurality of entities is disclosed. The computing system can be configured to input an entity profile that describes a preference and/or demand of a simulated entity into a reinforcement learning agent model and receive, as an output of the reinforcement learning agent model, an allocation output that describes a resource allocation for the simulated entity. The computing system can select one or more resources based on the resource allocation described by the allocation output and provide the resource(s) to an entity model that is configured to simulate a simulated response output that describes a response of the simulated entity. The computing system can receive, as an output of the entity model, the simulated response output and update a resource profile that describes the at least one resource and/or the entity profile based on the simulated response output.Type: ApplicationFiled: February 28, 2019Publication date: August 6, 2020Inventors: Tze Way Eugene Ie, Sanmit Santosh Narvekar, Craig Edgar Boutilier
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Patent number: 10713585Abstract: Systems and techniques are provided for template exploration in a large-scale machine learning system. A method may include obtaining multiple base templates, each base template comprising multiple features. A template performance score may be obtained for each base template and a first base template may be selected from among the multiple base templates based on the template performance score of the first base template. Multiple cross-templates may be constructed by generating a cross-template of the selected first base template and each of the multiple base templates. Performance of a machine learning model may be tested based on each cross-template to generate a cross-template performance score for each of the cross-templates. A first cross-template may be selected from among the multiple cross-templates based on the cross-template performance score of the cross-template. Accordingly, the first cross-template may be added to the machine learning model.Type: GrantFiled: December 16, 2013Date of Patent: July 14, 2020Assignee: Google LLCInventors: Tal Shaked, Tushar Deepak Chandra, James Vincent McFadden, Yoram Singer, Tze Way Eugene Ie
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Publication number: 20200151614Abstract: Systems and techniques are provided for template exploration in a large-scale machine learning system. A method may include obtaining multiple base templates, each base template comprising multiple features. A template performance score may be obtained for each base template and a first base template may be selected from among the multiple base templates based on the template performance score of the first base template. Multiple cross-templates may be constructed by generating a cross-template of the selected first base template and each of the multiple base templates. Performance of a machine learning model may be tested based on each cross-template to generate a cross-template performance score for each of the cross-templates. A first cross-template may be selected from among the multiple cross-templates based on the cross-template performance score of the cross-template. Accordingly, the first cross-template may be added to the machine learning model.Type: ApplicationFiled: December 16, 2013Publication date: May 14, 2020Applicant: Google Inc.Inventors: Tal Shaked, Tushar Deepak Chandra, James Vincent McFadden, Yoram Singer, Tze Way Eugene Ie