Patents by Inventor Alok Kothari

Alok Kothari 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: 11348130
    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods to generate sketches for clearing-bid values and bid-success rates based on multi-dimensional targeting criteria for a digital-content campaign and dynamically determine predicted values for the digital-content campaign based on the sketches. To illustrate, the disclosed systems can use a running-average-tuple-sketch to generate tuple sketches of historical clearing-bid values and tuple sketches of historical bid-success-rates from historical auction data. Based on the tuple sketches, the disclosed systems can determine one or more of a predicted cost per quantity of impressions, a predicted number of impressions, or a predicted expenditure for the digital-content campaign—according to user-input targeting criteria and expenditure constraints.
    Type: Grant
    Filed: August 17, 2020
    Date of Patent: May 31, 2022
    Assignee: Adobe Inc.
    Inventors: Chih Hsin Hsueh, Viswanathan Swaminathan, Venkata Karthik Penikalapati, Seth Olson, Michael Schiff, Gang Wu, Daniel Pang, Alok Kothari
  • Publication number: 20220051274
    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods to generate sketches for clearing-bid values and bid-success rates based on multi-dimensional targeting criteria for a digital-content campaign and dynamically determine predicted values for the digital-content campaign based on the sketches. To illustrate, the disclosed systems can use a running-average-tuple-sketch to generate tuple sketches of historical clearing-bid values and tuple sketches of historical bid-success-rates from historical auction data. Based on the tuple sketches, the disclosed systems can determine one or more of a predicted cost per quantity of impressions, a predicted number of impressions, or a predicted expenditure for the digital-content campaign—according to user-input targeting criteria and expenditure constraints.
    Type: Application
    Filed: August 17, 2020
    Publication date: February 17, 2022
    Inventors: Chih Hsin Hsueh, Viswanathan Swaminathan, Venkata Karthik Penikalapati, Seth Olson, Michael Schiff, Gang Wu, Daniel Pang, Alok Kothari
  • Publication number: 20210374809
    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.
    Type: Application
    Filed: August 16, 2021
    Publication date: December 2, 2021
    Inventors: Somdeb Sarkhel, Saayan Mitra, Jiatong Xie, Alok Kothari
  • Patent number: 11127050
    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.
    Type: Grant
    Filed: November 18, 2019
    Date of Patent: September 21, 2021
    Assignee: Adobe Inc.
    Inventors: Somdeb Sarkhel, Saayan Mitra, Jiatong Xie, Alok Kothari
  • Publication number: 20210150585
    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.
    Type: Application
    Filed: November 18, 2019
    Publication date: May 20, 2021
    Inventors: Somdeb Sarkhel, Saayan Mitra, Jiatong Xie, Alok Kothari