Patents by Inventor Michal HYRC

Michal HYRC 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).

  • AUTOMATIC SEGMENTATION USING HIERARCHICAL TIMESERIES ANALYSIS
    Publication number: 20240394416
    Abstract: Methods and systems are disclosed for using a feature hierarchy with multiple levels with a different number of features at different levels to segment a dataset. The mechanism may use the first level of the hierarchy to segment a dataset into multiple datasets and then generate a timeseries dataset for each segment. Those timeseries datasets may be input into an anomaly detection model to identify a number of anomalies detected within those segments. Based on the number of anomalies not reaching a threshold, a second level of the hierarchy may be used to segment the dataset. Those segments may be input into the anomaly detection model to determine a number of anomalies for the second level. This process may continue until a level of the hierarchy is determined such that the number of anomalies reaches the threshold. The mechanism may then generate a security rule to deal with the anomalies.
    Type: Application
    Filed: August 1, 2024
    Publication date: November 28, 2024
    Applicant: Capital One Services, LLC
    Inventors: Adam BEAUREGARD, Michal HYRC, Peter Gaspare TERRANA, Vannia GONZALEZ MACIAS
  • Automatic segmentation using hierarchical timeseries analysis
    Patent number: 12079375
    Abstract: Methods and systems are disclosed for using a feature hierarchy with multiple levels with a different number of features at different levels to segment a dataset. The mechanism may use the first level of the hierarchy to segment a dataset into multiple datasets and then generate a timeseries dataset for each segment. Those timeseries datasets may be input into an anomaly detection model to identify a number of anomalies detected within those segments. Based on the number of anomalies not reaching a threshold, a second level of the hierarchy may be used to segment the dataset. Those segments may be input into the anomaly detection model to determine a number of anomalies for the second level. This process may continue until a level of the hierarchy is determined such that the number of anomalies reaches the threshold. The mechanism may then generate a security rule to deal with the anomalies.
    Type: Grant
    Filed: May 25, 2022
    Date of Patent: September 3, 2024
    Assignee: Capital One Services, LLC
    Inventors: Adam Beauregard, Michal Hyrc, Peter Gaspare Terrana, Vannia Gonzalez Macias
  • AUTOMATIC SEGMENTATION USING HIERARCHICAL TIMESERIES ANALYSIS
    Publication number: 20230385456
    Abstract: Methods and systems are disclosed for using a feature hierarchy with multiple levels with a different number of features at different levels to segment a dataset. The mechanism may use the first level of the hierarchy to segment a dataset into multiple datasets and then generate a timeseries dataset for each segment. Those timeseries datasets may be input into an anomaly detection model to identify a number of anomalies detected within those segments. Based on the number of anomalies not reaching a threshold, a second level of the hierarchy may be used to segment the dataset. Those segments may be input into the anomaly detection model to determine a number of anomalies for the second level. This process may continue until a level of the hierarchy is determined such that the number of anomalies reaches the threshold. The mechanism may then generate a security rule to deal with the anomalies.
    Type: Application
    Filed: May 25, 2022
    Publication date: November 30, 2023
    Applicant: Capital One Services, LLC
    Inventors: Adam BEAUREGARD, Michal HYRC, Peter Gaspare TERRANA, Vannia GONZALEZ MACIAS