Degree-Quant: Quantization-Aware Training for Graph Neural Networks.
Shyam Anil TailorJavier Fernández-MarquésNicholas Donald LanePublished in: ICLR (2021)
Keyphrases
- neural network
- training process
- training algorithm
- feed forward neural networks
- feedforward neural networks
- multi layer perceptron
- artificial neural networks
- pattern recognition
- neural network training
- graph representation
- genetic algorithm
- graph structure
- backpropagation algorithm
- graph theory
- graph model
- neural network structure
- neural nets
- random walk
- back propagation
- neural network model
- error back propagation
- training set
- recurrent networks
- graph theoretic
- training samples
- test set
- structured data
- directed graph
- training phase
- graph partitioning
- training examples
- multi layer
- fault diagnosis
- supervised learning
- clustering coefficient
- data sets
- connected components
- degree distribution
- computational complexity
- image segmentation