Patents by Inventor Elliott Yama

Elliott Yama 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: 11455373
    Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.
    Type: Grant
    Filed: October 31, 2019
    Date of Patent: September 27, 2022
    Assignee: Apttus Corporation
    Inventors: Kirk G. Krappé, Neehar Giri, Man Chan, Isabelle Chai, Rahul Choudhry, Kitae Kim, Stanley Poon, Brian Li, Geeta Deodhar, Elliott Yama
  • Patent number: 10783575
    Abstract: The present disclosure describes a system, method, and computer program for creating and deploying prepackaged, predictive and prescriptive analytics modules for use with a quote-to-cash application. When deployed, the prepackaged analytics modules execute seamlessly, from the user's perspective, with the quote-to-cash application to provide predictions, recommendations, or other data-driven insights at one or more places in the quote-to-cash process. The modules are created by leveraging a pre-defined transactional data model that is native to the quote-to-cash application. A separate instance of the module is created for each customer that deploys a module. A customer's instance of the module is automatically retrained with the customer's own quote-to-cash data during the deployment phase by retrieving customer data matching metadata definitions predefined by the quote-to-cash application.
    Type: Grant
    Filed: July 1, 2016
    Date of Patent: September 22, 2020
    Assignee: Apttus Corporation
    Inventors: Kirk Gary Krappe, Neehar Giri, Geeta Deodhar, Elliott Yama
  • Publication number: 20200065354
    Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.
    Type: Application
    Filed: October 31, 2019
    Publication date: February 27, 2020
    Inventors: Kirk G. Krappé, Neehar Giri, Man Chan, Isabelle Chai, Rahul Choudhry, Kitae Kim, Stanley Poon, Brian Li, Geeta Deodhar, Elliott Yama
  • Patent number: 10521491
    Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.
    Type: Grant
    Filed: June 6, 2017
    Date of Patent: December 31, 2019
    Assignee: Apttus Corporation
    Inventors: Kirk G. Krappé, Neehar Giri, Man Chan, Isabelle Chai, Rahul Choudhry, Kitae Kim, Stanley Poon, Brian Li, Geeta Deodhar, Elliott Yama
  • Publication number: 20180349324
    Abstract: The present disclosure describes a system, method, and computer program for real-time and computationally efficient calculation of a recommended value range for a quote variable, such as price, discount, volume, or closing time. The system uses the highest-density interval (HDI) of probability density function (PDF) as a recommended or suggested value range for a quote variable. PDFs for the quote variable are precomputed for groups of related inputs, and each PDF is summarized as an array of discrete points. A dimension reduction technique is applied to the PDF inputs in both the training and real-time (non-training) phases to reduce the number of possible combinations of PDFs. During a quote-creation process, a PDF look-up table enables the system to efficiently identify an applicable PDF from the group of precomputed PDFs based on reduced input values.
    Type: Application
    Filed: June 6, 2017
    Publication date: December 6, 2018
    Inventors: Kirk G. Krappé, Neehar Giri, Man Chan, Isabelle Chai, Rahul Choudhry, Kitae Kim, Stanley Poon, Brian Li, Geeta Deodhar, Elliott Yama