公开(公告)号：US11800167B2

公开(公告)日：2023-10-24

申请号：US17515225

申请日：2021-10-29

Applicant: Roku, Inc.

Inventor： Amit Paliwal ,  Andrey Marsavin ,  Govind Vaidya ,  Wim Michiels ,  Beth Teresa Logan ,  Zheng Han ,  Tapan Oza ,  Vijay Anand Raghavan

IPC: H04N21/2662 ,  H04N21/24 ,  G06N20/00 ,  H04N21/25

CPC classification number: H04N21/2662 ,  G06N20/00 ,  H04N21/2401 ,  H04N21/251

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%.

公开(公告)号：US20230421831A1

公开(公告)日：2023-12-28

申请号：US18462635

申请日：2023-09-07

Applicant: ROKU, INC.

Inventor： Amit Paliwal ,  Andrey Marsavin ,  Govind Vaidya ,  Wim Michiels ,  Beth Teresa Logan ,  Zheng Han ,  Tapan Oza ,  Vijay Anand Raghavan

IPC: H04N21/2662 ,  H04N21/24 ,  G06N20/00 ,  H04N21/25

CPC classification number: H04N21/2662 ,  H04N21/2401 ,  G06N20/00 ,  H04N21/251

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%.

公开(公告)号：US20230351348A1

公开(公告)日：2023-11-02

申请号：US18339419

申请日：2023-06-22

Applicant: Roku, Inc.

Inventor： Sayan Maity ,  Christopher Carl Underwood ,  Beth Teresa Logan ,  Sreeram Srinivasan ,  Shanshan Tuo ,  Pradeep Reddy ,  Vijay Anand Raghavan ,  Raviteja Gunda ,  Shih-Ting Liu ,  Thong Le Nguyen

IPC: G06Q20/10 ,  G06Q20/12 ,  G06Q20/14 ,  G06Q20/40

CPC classification number: G06Q20/102 ,  G06Q20/123 ,  G06Q20/14 ,  G06Q20/401

Abstract: A method may include determining a combination of values of attributes represented by reference data associated with payment transaction by training a machine learning model based on an association between (i) respective values of the attributes and (ii) the payment transactions having a given result. The combination may be correlated with having the given result. The method may also include selecting a subset of the payment transactions that is associated with the combination of values. The method may additionally include determining a first rate at which payment transactions of the subset have the given result during a first time period and a second rate at which one or more payment transactions associated with the combination have the given result during a second time period, and generating an indication that the two rates differ.

公开(公告)号：US12137265B2

公开(公告)日：2024-11-05

申请号：US18462635

申请日：2023-09-07

Applicant: ROKU, INC.

Inventor： Amit Paliwal ,  Andrey Marsavin ,  Govind Vaidya ,  Wim Michiels ,  Beth Teresa Logan ,  Zheng Han ,  Tapan Oza ,  Vijay Anand Raghavan

IPC: H04N21/2662 ,  G06N5/01 ,  G06N20/00 ,  G06N20/20 ,  H04N21/24 ,  H04N21/25 ,  H04N21/44 ,  H04N21/442 ,  H04N21/845

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%.

公开(公告)号：US20230276080A1

公开(公告)日：2023-08-31

申请号：US17652875

申请日：2022-02-28

Applicant: Roku, Inc.

Inventor： Suvrath V. Penmetcha ,  Le Zhang ,  Vijay Anand Raghavan ,  Beth Teresa Logan ,  Kevin Henely ,  Sahib Bal ,  Sayan Maity

IPC: H04N21/226 ,  G06K9/62 ,  G06N5/00

CPC classification number: H04N21/226 ,  G06K9/6262 ,  G06N5/003

Abstract: A method may include determining a combination of values of attributes represented by reference data associated with computing devices by training a machine learning model based on an association between (i) respective values of the attributes and (ii) the computing devices entering a device state. The combination may be correlated with entry into the device state. The method may also include selecting a subset of the computing devices that is associated with the combination of values. The method may additionally include determining a first rate at which computing devices of the subset have entered the device state during a first time period and a second rate at which one or more computing devices associated with the combination have entered the device state during a second time period, and generating an indication that the two rates differ.