Patents by Inventor Balaji Srinivasa Rao Paladugu
Balaji Srinivasa Rao Paladugu 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: 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: 20230289662Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.Type: ApplicationFiled: May 21, 2023Publication date: September 14, 2023Inventors: Shengjun Pan, Tian Zhou, Brendan Kitts, Hao He, Bharatbhushan Shetty, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Guitekin, Balaji Srinivasa Rao Paladugu, Jianlong Zhang, Sneha Thomas, Aaron Flores
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Publication number: 20230281512Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.Type: ApplicationFiled: May 15, 2023Publication date: September 7, 2023Inventors: Tian Zhou, Djoefje Gligorijevic, Bharatbhushan Shetty, Junwei Pan, Brendan kitts, Shengjun Pan, Balaji Srinivasa Rao Paladugu, Sneha Thomas, Aaron Flores
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Patent number: 11657326Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.Type: GrantFiled: August 17, 2020Date of Patent: May 23, 2023Assignee: YAHOO AD TECH LLCInventors: Shengjun Pan, Tian Zhou, Brendan Kitts, Hao He, Bharatbhushan Shetty, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Gultekin, Balaji Srinivasa Rao Paladugu, Jianlong Zhang, Sneha Thomas, Aaron Flores
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Patent number: 11651284Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.Type: GrantFiled: August 17, 2020Date of Patent: May 16, 2023Assignee: YAHOO AD TECH LLCInventors: Tian Zhou, Djordje Gligorijevic, Bharatbhushan Shetty, Junwei Pan, Brendan Kitts, Shengjun Pan, Balaji Srinivasa Rao Paladugu, Sneha Thomas, Aaron Flores
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Publication number: 20230012700Abstract: A computer-implemented method for optimizing electronic content delivery for non-measurable users includes receiving a feature vector for each electronic content impression opportunity, receiving a feature vector for each delivered item of electronic content for measurable users, receiving an in-target indication for each delivered item of electronic content for measurable users, estimating a probability that an electronic content impression opportunity with a specified feature vector will meet targeting requirements based on the received feature vectors and the received in-target indications, receiving an in-target threshold value, generating an in-target rate control signal based on a number of total delivered items of electronic content for measurable users and a number of in-target delivered items of electronic content for measurable users, determining whether the estimated probability is greater than the in-target rate control signal, and generating conditions for delivering a new item of electronic contType: ApplicationFiled: July 13, 2021Publication date: January 19, 2023Inventors: Niklas KARLSSON, Ravi KANT, Qian SANG, Balaji Srinivasa Rao PALADUGU, Aaron FLORES, Tularam BAN, Hirakendu DAS, Maxim SVIRIDENKO
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Publication number: 20220414493Abstract: The disclosed systems and methods provide a novel framework that provides mechanisms for predicting user actions of provided digital content based on an aggregation of user data. Conventional user tracking, and action prediction and recommendation systems have a lifespan that is ending in the short term due to new privacy laws. The disclosed framework enables personalized recommendations to be formulated for specific users based on an imputation from user data aggregated from a plurality of users. While anonymity is maintained, recommendations for predicted actions can be provided to the users and/or the providers of the content. The disclosed framework can scale the aggregated user data using a Naïve Bayes classifier, from which a logistic regression modeling can be performed to determine the predicted recommendation.Type: ApplicationFiled: June 9, 2021Publication date: December 29, 2022Inventors: Ravi KANT, Maxim SVIRIDENKO, Hirakendu DAS, Balazs SZORENYI, Xiangkun SHEN, Mikhail KUZNETSOV, Aaron FLORES, Ben SHAHSHAHANI, Balaji Srinivasa Rao PALADUGU
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Publication number: 20220051130Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.Type: ApplicationFiled: August 17, 2020Publication date: February 17, 2022Inventors: Tian Zhou, Djordje Gligorijevic, Bharatbhushan Shetty, Junwei Pan, Brendan Kitts, Shengjun Pan, Balaji Srinivasa Rao Paladugu, Sneha Thomas, Aaron Flores
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Publication number: 20220051131Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.Type: ApplicationFiled: August 17, 2020Publication date: February 17, 2022Inventors: Shengjun Pan, Tian Zhou, Brendan Kitts, Hao He, Bharatbhushan Shetty, Djordje Gligorijevic, Junwei Pan, Tingyu Mao, San Gultekin, Balaji Srinivasa Rao Paladugu, Jianlong Zhang, Sneha Thomas, Aaron 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