Patents by Inventor Ashot ASLANYAN

Ashot ASLANYAN 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).

  • SERVICE LABELING USING SEMI-SUPERVISED LEARNING
    Publication number: 20230262114
    Abstract: The disclosure provides an approach for workload labeling and identification of known or custom applications. Embodiments include determining a plurality of sets of features comprising a respective set of features for each respective workload of a first subset of a plurality of workloads. Embodiments include identifying a group of workloads based on similarities among the plurality of sets of features. Embodiments include receiving label data from a user comprising a label for the group of workloads. Embodiments include associating the label with each workload of the group of workloads to produce a training data set. Embodiments include using the training data set to train a model to output labels for input workloads. Embodiments include determining a label for a given workload of the plurality of workloads by inputting features of the given workload to the model.
    Type: Application
    Filed: April 26, 2023
    Publication date: August 17, 2023
    Inventors: Alok TIAGI, Farzad GHANNADIAN, Karen HAYRAPETYAN, Laxmikant Vithal GUNDA, Sunitha KRISHNA, Ashot ASLANYAN, Anirban SENGUPTA
  • Service labeling using semi-supervised learning
    Patent number: 11659026
    Abstract: The disclosure provides an approach for workload labeling and identification of known or custom applications. Embodiments include determining a plurality of sets of features comprising a respective set of features for each respective workload of a first subset of a plurality of workloads. Embodiments include identifying a group of workloads based on similarities among the plurality of sets of features. Embodiments include receiving label data from a user comprising a label for the group of workloads. Embodiments include associating the label with each workload of the group of workloads to produce a training data set. Embodiments include using the training data set to train a model to output labels for input workloads. Embodiments include determining a label for a given workload of the plurality of workloads by inputting features of the given workload to the model.
    Type: Grant
    Filed: April 22, 2020
    Date of Patent: May 23, 2023
    Assignee: VMWARE, INC.
    Inventors: Alok Tiagi, Farzad Ghannadian, Karen Hayrapetyan, Laxmikant Vithal Gunda, Sunitha Krishna, Ashot Aslanyan, Anirban Sengupta
  • SERVICE LABELING USING SEMI-SUPERVISED LEARNING
    Publication number: 20210336899
    Abstract: The disclosure provides an approach for workload labeling and identification of known or custom applications. Embodiments include determining a plurality of sets of features comprising a respective set of features for each respective workload of a first subset of a plurality of workloads. Embodiments include identifying a group of workloads based on similarities among the plurality of sets of features. Embodiments include receiving label data from a user comprising a label for the group of workloads. Embodiments include associating the label with each workload of the group of workloads to produce a training data set. Embodiments include using the training data set to train a model to output labels for input workloads. Embodiments include determining a label for a given workload of the plurality of workloads by inputting features of the given workload to the model.
    Type: Application
    Filed: April 22, 2020
    Publication date: October 28, 2021
    Inventors: Alok TIAGI, Farzad GHANNADIAN, Karen HAYRAPETYAN, Laxmikant Vithal GUNDA, Sunitha KRISHNA, Ashot ASLANYAN, Anirban SENGUPTA