Patents by Inventor Aravind BAPPANADU

Aravind BAPPANADU 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).

  • Secure cloud-based machine learning without sending original data to the cloud
    Patent number: 11568257
    Abstract: Method and system for training a neural network. The neural network is split into first and second portions. A k-layer first portion is sent to a client training/inference engine and the second portion is retained by a server training/inference engine. At the splitting point, the kth layer is a one-way function in output computation has a number of nodes that are less than any other layer of the first portion. The client training/inference engine trains the first portion with input data in a set of training data. The server training/inference engine receives a batch of outputs from the client training and applies them to the second portion to train the entire neural network.
    Type: Grant
    Filed: May 20, 2019
    Date of Patent: January 31, 2023
    Assignee: VMWARE, INC.
    Inventors: Lan Vu, Dimitrios Skarlatos, Aravind Bappanadu, Hari Sivaraman, Uday Kurkure, Vijayaraghavan Soundararajan
  • SECURE CLOUD-BASED MACHINE LEARNING WITHOUT SENDING ORIGINAL DATA TO THE CLOUD
    Publication number: 20200372360
    Abstract: Method and system for training a neural network. The neural network is split into first and second portions. A k-layer first portion is sent to a client training/inference engine and the second portion is retained by a server training/inference engine. At the splitting point, the kth layer is a one-way function in output computation has a number of nodes that are less than any other layer of the first portion. The client training/inference engine trains the first portion with input data in a set of training data. The server training/inference engine receives a batch of outputs from the client training and applies them to the second portion to train the entire neural network.
    Type: Application
    Filed: May 20, 2019
    Publication date: November 26, 2020
    Inventors: Lan VU, Dimitrios SKARLATOS, Aravind BAPPANADU, Hari SIVARAMAN, Uday KURKURE, Vijayaraghavan SOUNDARARAJAN