Patents by Inventor Sameer Vadera

Sameer Vadera 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).

  • Machine learning temporal allocator
    Patent number: 10425353
    Abstract: A method and system for determining of timing for vector following a branched processing model is disclosed. A data source is mined to determine event vectors from a large number of cases that follow a branched processing model. Current event vectors are compared to the mined event vectors with machine learning to predict future nodes for the current event vectors. Historical temporal spacing for the mined event vectors are used to predict temporal position for the current event vector in the future.
    Type: Grant
    Filed: April 8, 2019
    Date of Patent: September 24, 2019
    Assignee: Triangle IP, Inc.
    Inventors: Sameer Vadera, Katherine S. Gaudry, Thomas D. Franklin
  • Machine learning resource allocator
    Patent number: 10257116
    Abstract: A method and system for allocation of resources is disclosed. A data source is mined to determine event vectors from a large number of cases that follow a branched processing model. Current event vectors are compared to the mined event vectors with machine learning to predict future nodes for the current event vectors. Historical resource allocations for the mined event vectors are used to determine resource allocation for the current event vector over time. Current event vectors are combined to produce a resource allocation curve showing past and future resources allocated.
    Type: Grant
    Filed: August 31, 2018
    Date of Patent: April 9, 2019
    Assignee: Triangle IP, Inc.
    Inventors: Sameer Vadera, Katherine S. Gaudry, Thomas D. Franklin
  • Machine learning resource allocator
    Patent number: 10069759
    Abstract: A method and system for allocation of resources is disclosed. Authenticated and unauthenticated data sources are mined to determine event vectors from a large number of cases that follow a branched processing model. A current event vector is compared to the mined event vectors with machine learning to predict future nodes for the current event vector. Historical resource allocations for the mined event vectors are used to determine resource allocation for the current event vector over time.
    Type: Grant
    Filed: January 29, 2018
    Date of Patent: September 4, 2018
    Assignee: TRIANGLE IP, INC.
    Inventors: Sameer Vadera, Katherine S. Gaudry, Thomas D. Franklin