Patents by Inventor Aaron Eliasib Flores
Aaron Eliasib Flores 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: 20240144315Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.Type: ApplicationFiled: January 8, 2024Publication date: May 2, 2024Inventors: Joel Barajas Zamora, Lakshmi Narayan Bhamidipati, Aaron Eliasib Flores, Benjamin Grant Jackson, Parag Bhattacharjee, Balaji Srinivasa Rao Paladugu
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Patent number: 11941669Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: GrantFiled: April 24, 2023Date of Patent: March 26, 2024Assignee: Yahoo Ad Tech LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11869033Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.Type: GrantFiled: December 9, 2019Date of Patent: January 9, 2024Assignee: Yahoo Ad Tech LLCInventors: Joel Barajas Zamora, Lakshmi Narayan Bhamidipati, Aaron Eliasib Flores, Benjamin Grant Jackson, Parag Bhattacharjee, Balaji Srinivasa Rao Paladugu
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Publication number: 20230334530Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: ApplicationFiled: June 26, 2023Publication date: October 19, 2023Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20230316337Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: ApplicationFiled: April 24, 2023Publication date: October 5, 2023Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11687978Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: GrantFiled: May 23, 2022Date of Patent: June 27, 2023Assignee: Yahoo Assets LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11636521Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: GrantFiled: March 9, 2022Date of Patent: April 25, 2023Assignee: YAHOO AD TECH LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220277354Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: ApplicationFiled: May 23, 2022Publication date: September 1, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220198526Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: ApplicationFiled: March 9, 2022Publication date: June 23, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11341541Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: GrantFiled: September 22, 2020Date of Patent: May 24, 2022Assignee: YAHOO ASSETS LLCInventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Patent number: 11295346Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: GrantFiled: September 22, 2020Date of Patent: April 5, 2022Assignee: VERIZON MEDIA INC.Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220092644Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.Type: ApplicationFiled: September 22, 2020Publication date: March 24, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20220092645Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.Type: ApplicationFiled: September 22, 2020Publication date: March 24, 2022Inventors: Junwei Pan, Tian Zhou, Aaron Eliasib Flores
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Publication number: 20210174389Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.Type: ApplicationFiled: December 9, 2019Publication date: June 10, 2021Inventors: Joel Barajas Zamora, Lakshmi Narayan Bhamidipati, Aaron Eliasib Flores, Benjamin Grant Jackson, Parag Bhattacharjee, Balaji Srinivasa Rao Paladugu