Patents by Inventor Michael Avrahamov

Michael Avrahamov 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).

  • Optimization for scalable analytics using time series models
    Patent number: 10949436
    Abstract: Techniques are described for optimizing scalability of analytics that use time-series models. In one or more embodiments, a stored time-series model includes a plurality of data points representing seasonal behavior in a training set of time-series data for at least one season. A target time for evaluating the time-series model is then determined, and the target time or one or more times relative to the target time are mapped to a subset of the plurality of data points. Based on the mapping, a trimmed version of the time-series model is generated by loading the subset of the plurality of data points into a cache, the subset of data points representing seasonal behavior in the training set of time-series data for a portion of the at least one season. A target set of time-series data may be evaluated suing the trimmed version of the time-series in the cache.
    Type: Grant
    Filed: February 22, 2018
    Date of Patent: March 16, 2021
    Assignee: Oracle International Corporation
    Inventors: Sampanna Shahaji Salunke, Dustin Garvey, Michael Avrahamov
  • OPTIMIZATION FOR SCALABLE ANALYTICS USING TIME SERIES MODELS
    Publication number: 20180246941
    Abstract: Techniques are described for optimizing scalability of analytics that use time-series models. In one or more embodiments, a stored time-series model includes a plurality of data points representing seasonal behavior in a training set of time-series data for at least one season. A target time for evaluating the time-series model is then determined, and the target time or one or more times relative to the target time are mapped to a subset of the plurality of data points. Based on the mapping, a trimmed version of the time-series model is generated by loading the subset of the plurality of data points into a cache, the subset of data points representing seasonal behavior in the training set of time-series data for a portion of the at least one season. A target set of time-series data may be evaluated suing the trimmed version of the time-series in the cache.
    Type: Application
    Filed: February 22, 2018
    Publication date: August 30, 2018
    Applicant: Oracle International Corporation
    Inventors: Sampanna Shahaji Salunke, Dustin Garvey, Michael Avrahamov