Degree-Quant: Quantization-Aware Training for Graph Neural Networks.
Shyam A. TailorJavier Fernández-MarquésNicholas D. LanePublished in: CoRR (2020)
Keyphrases
- neural network
- training process
- training algorithm
- backpropagation algorithm
- feedforward neural networks
- feed forward neural networks
- multi layer perceptron
- neural network training
- pattern recognition
- random walk
- back propagation
- graph structure
- error back propagation
- training phase
- feed forward
- self organizing maps
- neural network structure
- training set
- radial basis function network
- artificial neural networks
- training samples
- genetic algorithm
- graph representation
- directed acyclic graph
- weighted graph
- graph matching
- multilayer perceptron
- recurrent neural networks
- multiresolution
- directed graph
- social networks
- degree distribution
- clustering coefficient
- random graphs
- neural nets
- structured data
- graph theoretic
- graph theory
- online learning
- fault diagnosis
- graph model
- graph mining
- training examples
- hidden layer