Patents by Inventor Tsuwang Hsieh

Tsuwang Hsieh 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).

  • Publication number: 20250112843
    Abstract: Securing and optimizing communications for a cloud service provider includes collecting connection summary information at network interface devices associated with host computing devices for a group of resources allocated to a customer of the cloud computing environment. The connection summary information includes local address information, remote address information, and data information, each connection established via the network interface devices. At least one communication graph is generated for the group of resources using the connection summary information. The graph includes nodes that represent communication resources of the group of resources and edges extending between nodes that characterize communication between the nodes. At least one analytics process is performed on data from the graph to identify at least one of a micro-segmentation strategy, a communication pattern, and a flow prediction for the group of resources.
    Type: Application
    Filed: September 28, 2023
    Publication date: April 3, 2025
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Sathiya Kumaran MANI, Tsuwang HSIEH, Ranveer CHANDRA, Srikanth KANDULA, Santiago Martin SEGARRA
  • Publication number: 20250088428
    Abstract: This document relates to automating detecting anomalies in network behavior of an application Generally, the disclosed techniques can obtain network flow data for an application. A machine learning model can be used to process the network flow data to detect anomalies. The machine learning model can be retrained over time to adapt to changing network behavior of the application. In some cases, a graph neural network is employed to detect the anomalies.
    Type: Application
    Filed: September 13, 2023
    Publication date: March 13, 2025
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Tsuwang HSIEH, Santiago Martin SEGARRA, Sathiya Kumaran MANI, Srikanth KANDULA, Michael Dean WONG
  • Publication number: 20250036375
    Abstract: This patent relates to automating network management. One example includes a graph analysis and manipulation tool configured to receive a natural language prompt relating to a network management activity. The graph analysis and manipulation tool is also configured to access a graph resource and to generate code that addresses the network management activity as a graph manipulation task.
    Type: Application
    Filed: December 22, 2023
    Publication date: January 30, 2025
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Tsuwang HSIEH, Sathiya Kumaran MANI, Ranveer CHANDRA, Srikanth KANDULA, Santiago Martin SEGARRA, Yajie ZHOU
  • Publication number: 20240096063
    Abstract: Systems and methods are provided for reusing and retraining an image recognition model for video analytics. The image recognition model is used for inferring a frame of video data that is captured at edge devices. The edge devices periodically or under predetermined conditions transmits a captured frame of video data to perform inferencing. The disclosed technology is directed to select an image recognition model from a model store for reusing or for retraining. A model selector uses a gating network model to determine ranked candidate models for validation. The validation includes iterations of retraining the image recognition model and stopping the iteration when a rate of improving accuracy by retraining becomes smaller than the previous iteration step. Retraining a model includes generating reference data using a teacher model and retraining the model using the reference data. Integrating reuse and retraining of models enables improvement in accuracy and efficiency.
    Type: Application
    Filed: December 9, 2022
    Publication date: March 21, 2024
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ganesh ANANTHANARAYANAN, Yuanchao SHU, Paramvir BAHL, Tsuwang HSIEH
  • Publication number: 20220414534
    Abstract: Systems and methods are provided for continuous learning of models across hierarchies under a multi-access edge computing. In particular, an on-premises edge server, using a model, generates inference data associated with captured stream data. A data drift determiner determines a data drift in the inference data by comparing the data against reference data generated using a golden model. The data drift indicates a loss of accuracy in the inference data. A gateway model maintains one or more models in a model cache for update the model. The gateway model instructs the one or more servers to train the new model. The gateway model transmits the trained model to update the model in the on-premises edge server. Training the new model includes determining an on-premises edge server with computing resources available to train the new model while generating other inference data for incoming stream data in the data analytic pipeline.
    Type: Application
    Filed: June 29, 2021
    Publication date: December 29, 2022
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ganesh ANANTHANARAYANAN, Yuanchao SHU, Paramvir BAHL, Tsuwang HSIEH
  • Publication number: 20220366300
    Abstract: A cloud-based service uses an offline training pipeline to categorize training data for machine learning (ML) models into various clusters. Incoming test data that is received by a data center or in a cloud environment is compared against the categorized training data to identify the appropriate ML model to assign the test data. The comparison of the test data is done in real-time using a similarity metric that takes into account spatial and temporal factors of the test data relative to the categorized training data.
    Type: Application
    Filed: May 17, 2021
    Publication date: November 17, 2022
    Inventors: Tsuwang HSIEH, Behnaz ARZANI, Ankur MALLICK
  • Patent number: 11354902
    Abstract: A method can include classifying, using a compressed and specialized convolutional neural network (CNN), an object of a video frame into classes, clustering the object based on a distance of a feature vector of the object to a feature vector of a centroid object of the cluster, storing top-k classes, a centroid identification, and a cluster identification, in response to receiving a query for objects of class X from a specific video stream, retrieving image data for each centroid of each cluster that includes the class X as one of the top-k classes, classifying, using a ground truth CNN (GT-CNN), the retrieved image data for each centroid, and for each centroid determined to be classified as a member of the class X providing image data for each object in each cluster associated with the centroid.
    Type: Grant
    Filed: May 15, 2020
    Date of Patent: June 7, 2022
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ganesh Ananthanarayanan, Paramvir Bahl, Peter Bodik, Tsuwang Hsieh, Matthai Philipose
  • Publication number: 20200334465
    Abstract: A method can include classifying, using a compressed and specialized convolutional neural network (CNN), an object of a video frame into classes, clustering the object based on a distance of a feature vector of the object to a feature vector of a centroid object of the cluster, storing top-k classes, a centroid identification, and a cluster identification, in response to receiving a query for objects of class X from a specific video stream, retrieving image data for each centroid of each cluster that includes the class X as one of the top-k classes, classifying, using a ground truth CNN (GT-CNN), the retrieved image data for each centroid, and for each centroid determined to be classified as a member of the class X providing image data for each object in each cluster associated with the centroid.
    Type: Application
    Filed: May 15, 2020
    Publication date: October 22, 2020
    Inventors: Ganesh Ananthanarayanan, Paramvir Bahl, Peter Bodik, Tsuwang Hsieh, Matthai Philipose
  • Patent number: 10685235
    Abstract: A method can include classifying, using a compressed and specialized convolutional neural network (CNN), an object of a video frame into classes, clustering the object based on a distance of a feature vector of the object to a feature vector of a centroid object of the cluster, storing top-k classes, a centroid identification, and a cluster identification, in response to receiving a query for objects of class X from a specific video stream, retrieving image data for each centroid of each cluster that includes the class X as one of the top-k classes, classifying, using a ground truth CNN (GT-CNN), the retrieved image data for each centroid, and for each centroid determined to be classified as a member of the class X providing image data for each object in each cluster associated with the centroid.
    Type: Grant
    Filed: May 4, 2018
    Date of Patent: June 16, 2020
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Ganesh Ananthanarayanan, Paramvir Bahl, Peter Bodik, Tsuwang Hsieh, Matthai Philipose
  • Publication number: 20190205649
    Abstract: A method can include classifying, using a compressed and specialized convolutional neural network (CNN), an object of a video frame into classes, clustering the object based on a distance of a feature vector of the object to a feature vector of a centroid object of the cluster, storing top-k classes, a centroid identification, and a cluster identification, in response to receiving a query for objects of class X from a specific video stream, retrieving image data for each centroid of each cluster that includes the class X as one of the top-k classes, classifying, using a ground truth CNN (GT-CNN), the retrieved image data for each centroid, and for each centroid determined to be classified as a member of the class X providing image data for each object in each cluster associated with the centroid.
    Type: Application
    Filed: May 4, 2018
    Publication date: July 4, 2019
    Inventors: Ganesh Ananthanarayanan, Paramvir Bahl, Peter Bodik, Tsuwang Hsieh, Matthai Philipose