Training Heterogeneous Graph Neural Networks using Bandit Sampling.
Ta-Yang WangRajgopal KannanViktor K. PrasannaPublished in: CIKM (2023)
Keyphrases
- neural network
- random sampling
- training process
- training algorithm
- feed forward neural networks
- feedforward neural networks
- pattern recognition
- backpropagation algorithm
- directed graph
- artificial neural networks
- graph representation
- recurrent networks
- back propagation
- neural network model
- multi layer perceptron
- graph structure
- recurrent neural networks
- weighted graph
- svm training
- neural network training
- training set
- training data
- neural network structure
- graph model
- radial basis function network
- error back propagation
- training phase
- multi layer
- graph theory
- graph matching
- feed forward
- training samples
- fuzzy logic
- genetic algorithm
- directed acyclic graph
- graph theoretic
- sampling algorithm
- sampling methods
- fault diagnosis
- training examples
- decision trees