Invention Grant
- Patent Title: Recurrent neural networks with diagonal and programming fluctuation to find energy global minima
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Application No.: US16260898Application Date: 2019-01-29
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Publication No.: US11599771B2Publication Date: 2023-03-07
- Inventor: Suhas Kumar , Thomas Van Vaerenbergh , John Paul Strachan
- Applicant: Hewlett Packard Enterprise Development LP
- Applicant Address: US TX Houston
- Assignee: Hewlett Packard Enterprise Development LP
- Current Assignee: Hewlett Packard Enterprise Development LP
- Current Assignee Address: US TX Houston
- Agency: Sheppard Mullin Richter & Hampton LLP
- Main IPC: G06N3/06
- IPC: G06N3/06 ; G06N3/08 ; G06N3/04 ; G06N3/063

Abstract:
Recurrent neural networks, and methods therefor, are provided with diagonal and programming fluctuation to find energy global minima. The method may include storing the matrix of weights in memory cells of a crossbar array of a recursive neural network prior to operation of the recursive neural network; altering the weights according to a probability distribution; setting the weights to non-zero values in at least one of the memory cells in a diagonal of the memory cells in the crossbar array; and operating the recursive neural network.
Public/Granted literature
- US20200242447A1 RECURRENT NEURAL NETWORKS WITH DIAGONAL AND PROGRAMMING FLUCTUATION TO FIND ENERGY GLOBAL MINIMA Public/Granted day:2020-07-30
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