US 2017/0364799 A1 · SIMPLIFYING APPARATUS AND SIMPLIFYING METHOD FOR NEURAL NETWORK

Abstract

An apparatus for deciding a simplification policy for a neural network is provided. The deciding apparatus has a plurality of artificial neurons, a receiving circuit, a memory, and a simplifying module. The plurality of artificial neurons are configured to form an original neural network. The receiving circuit receives a set of sample for training the original neural network. The memory is used for recording a plurality of learnable parameters for the original neural network. After the original neural network has been trained with the set of sample, the simplifying module abandons a part of neuron connections in the original neural network based on the learnable parameters recorded by the memory. The simplifying module accordingly decides the structure of a simplified neural network and a plurality of learnable parameters for the simplified neural network.

Claims27

Dependent claims

A simplifying apparatus for a neural network, comprising:

a plurality of artificial neurons configured to form an original neural network;
a receiving circuit, coupled to the plurality of neurons, for receiving a set of sample for training the original neural network;
a memory, coupled to the plurality of neurons, for recording a plurality of learnable parameters of the original neural network;
and
a simplifying module coupled to the memory, after the original neural network has been trained with the set of sample, the simplifying module abandoning a part of neuron connections in the original neural network based on the plurality of learnable parameters recorded in the memory, the simplifying module accordingly deciding the structure of a simplified neural network.

2 more elements

A non-transitory computer-readable storage medium encoded with a computer program for simplifying a neural network, the computer program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

(a) training an original neural network formed by a plurality of artificial neurons with a set of sample, so as to decide a plurality of learnable parameters of the original neural network;
and
(b) based on the plurality of learnable parameters decided in operation (a), abandoning a part of neuron connections in the original neural network, so as to decide the structure of a simplified neural network.

Dependencies are inferred from the claim text.

Simplifying apparatus and simplifying method for neural network

Life of this patent

Simplifying apparatus and simplifying method for neural network

Life of this patent

Abstract

Claims27