Invention Grant
- Patent Title: Learning non-differentiable weights of neural networks using evolutionary strategies
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Application No.: US16751169Application Date: 2020-01-23
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Publication No.: US11676035B2Publication Date: 2023-06-13
- Inventor: Karel Lenc , Karen Simonyan , Tom Schaul , Erich Konrad Elsen
- Applicant: DeepMind Technologies Limited
- Applicant Address: GB London
- Assignee: DeepMind Technologies Limited
- Current Assignee: DeepMind Technologies Limited
- Current Assignee Address: GB London
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/086 ; G06N3/044

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. The neural network has a plurality of differentiable weights and a plurality of non-differentiable weights. One of the methods includes determining trained values of the plurality of differentiable weights and the non-differentiable weights by repeatedly performing operations that include determining an update to the current values of the plurality of differentiable weights using a machine learning gradient-based training technique and determining, using an evolution strategies (ES) technique, an update to the current values of a plurality of distribution parameters.
Public/Granted literature
- US20200234142A1 LEARNING NON-DIFFERENTIABLE WEIGHTS OF NEURAL NETWORKS USING EVOLUTIONARY STRATEGIES Public/Granted day:2020-07-23
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