Patent · US Active

System and method of a monotone operator neural network

US11468276B2 · kind B2 · utility

0Cited by

3References

20Claims

0Family size

Assignee

Robert Bosch GmbH · DE

Inventors

Ezra Winston · Pittsburgh, US
Jeremy Zieg Kolter · Pittsburgh, US
Anit Kumar Sahu · Pittsburgh, US

Key dates

Filing date	Apr 16, 2020
Grant date	Oct 11, 2022
Priority date	—
Expiry date	Apr 8, 2041

Classification

Technology area (CPC G)Physics
CPC primaryG06V20/56
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

A system for training a neural work that includes an input interface for accessing input data for the neural network and a processor in communication with the input interface. The processor is programmed to receive input at the neural network and output a trained neural networking utilizing a forward prorogation and a backward propagation, wherein the forward propagation includes utilizing a root-finding procedure to identify a fixed point associated with one or more parameters of the neural network, wherein the backward propagation includes identifying a derivative of a loss associated with the parameters of the network.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.