Patents by Inventor Trung Dang

Trung Dang 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).

  • Ascertaining and/or mitigating extent of effective reconstruction, of predictions, from model updates transmitted in federated learning
    Patent number: 12688467
    Abstract: Implementations relate to ascertaining to what extent predictions, generated using a machine learning model, can be effectively reconstructed from model updates, where the model updates are generated based on those predictions and based on applying a particular loss technique (e.g., a particular cross-entropy loss technique). Some implementations disclosed generate measures that each indicate a degree of conformity between a corresponding reconstruction, generated using a corresponding model update, and a corresponding prediction. In some of those implementations, the measures are utilized in determining whether to utilize the particular loss technique (utilized in generating the model updates) in federated learning of the machine learning model and/or of additional machine learning model(s).
    Type: Grant
    Filed: November 24, 2021
    Date of Patent: July 21, 2026
    Assignee: GOOGLE LLC
    Inventors: Om Dipakbhai Thakkar, Trung Dang, Swaroop Indra Ramaswamy, Rajiv Mathews, Françoise Beaufays
  • ASCERTAINING AND/OR MITIGATING EXTENT OF EFFECTIVE RECONSTRUCTION, OF PREDICTIONS, FROM MODEL UPDATES TRANSMITTED IN FEDERATED LEARNING
    Publication number: 20220383204
    Abstract: Implementations relate to ascertaining to what extent predictions, generated using a machine learning model, can be effectively reconstructed from model updates, where the model updates are generated based on those predictions and based on applying a particular loss technique (e.g., a particular cross-entropy loss technique). Some implementations disclosed generate measures that each indicate a degree of conformity between a corresponding reconstruction, generated using a corresponding model update, and a corresponding prediction. In some of those implementations, the measures are utilized in determining whether to utilize the particular loss technique (utilized in generating the model updates) in federated learning of the machine learning model and/or of additional machine learning model(s).
    Type: Application
    Filed: November 24, 2021
    Publication date: December 1, 2022
    Inventors: Om Dipakbhai Thakkar, Trung Dang, Swaroop Indra Ramaswamy, Rajiv Mathews, Françoise Beaufays