Patents by Inventor Elad Hofer

Elad Hofer 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).

  • Activation function approximation in deep neural networks using rectified-linear-unit function
    Patent number: 11468147
    Abstract: A computational apparatus for implementing a neural network model having multiple neurons that evaluate an activation function, the apparatus including a memory and circuitry. The memory is configured to hold values of a difference-function, each value being a respective difference between the activation function and a predefined baseline function. The circuitry is configured to evaluate the neural network model, including, for at least one of the neurons: evaluate the baseline function at the argument, retrieve from the memory one or more values of the difference-function responsively to the argument, and evaluate the activation function at the argument based on the baseline function at the argument and on the one or more values of the difference-function.
    Type: Grant
    Filed: February 24, 2020
    Date of Patent: October 11, 2022
    Assignee: HABANA LABS LTD.
    Inventors: Elad Hofer, Sergei Gofman, Shlomo Raikin