Patents by Inventor Tapan OZA

Tapan OZA 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 FOR ADAPTIVE BITRATE SELECTION
    Publication number: 20230421831
    Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for modifying one or more parameters of a data streaming bitrate selection algorithm based on machine learning. An example embodiment operates by training and operating a first machine learning model to predict a sustainable network bandwidth. A second machine learning model is trained to receive the sustainable network bandwidth and predict a likelihood that this network bandwidth will not empty a data buffer of streaming data. A bitrate is selected based on the likelihood being below a threshold percentage, such as 50%.
    Type: Application
    Filed: September 7, 2023
    Publication date: December 28, 2023
    Applicant: ROKU, INC.
    Inventors: Amit Paliwal, Andrey Marsavin, Govind Vaidya, Wim Michiels, Beth Teresa Logan, Zheng Han, Tapan Oza, Vijay Anand Raghavan
  • Machine learning for adaptive bitrate selection
    Patent number: 11800167
    Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for modifying one or more parameters of a data streaming bitrate selection algorithm based on machine learning. An example embodiment operates by training and operating a first machine learning model to predict a sustainable network bandwidth. A second machine learning model is trained to receive the sustainable network bandwidth and predict a likelihood that this network bandwidth will not empty a data buffer of streaming data. A bitrate is selected based on the likelihood being below a threshold percentage, such as 50%.
    Type: Grant
    Filed: October 29, 2021
    Date of Patent: October 24, 2023
    Assignee: ROKU, INC.
    Inventors: Amit Paliwal, Andrey Marsavin, Govind Vaidya, Wim Michiels, Beth Teresa Logan, Zheng Han, Tapan Oza, Vijay Anand Raghavan
  • MACHINE LEARNING FOR ADAPTIVE BITRATE SELECTION
    Publication number: 20230133880
    Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for modifying one or more parameters of a data streaming bitrate selection algorithm based on machine learning. An example embodiment operates by training and operating a first machine learning model to predict a sustainable network bandwidth. A second machine learning model is trained to receive the sustainable network bandwidth and predict a likelihood that this network bandwidth will not empty a data buffer of streaming data. A bitrate is selected based on the likelihood being below a threshold percentage, such as 50%.
    Type: Application
    Filed: October 29, 2021
    Publication date: May 4, 2023
    Inventors: Amit PALIWAL, Andrey MARSAVIN, Govind VAIDYA, Wim MICHIELS, Beth Teresa LOGAN, Zheng HAN, Tapan OZA, Vijay Anand RAGHAVAN