Training Sparse Graph Neural Networks via Pruning and Sprouting.
Xueqi MaXingjun MaSarah M. ErfaniJames BaileyPublished in: SDM (2024)
Keyphrases
- neural network
- avoid overfitting
- training process
- training algorithm
- feedforward neural networks
- pattern recognition
- multi layer perceptron
- neural network training
- graph representation
- backpropagation algorithm
- feed forward neural networks
- back propagation
- graph structure
- gaussian graphical models
- error back propagation
- directed acyclic graph
- high dimensional
- search space
- directed graph
- neural network model
- multilayer perceptron
- pruning method
- structured data
- training phase
- graph model
- support vector machine
- genetic algorithm
- artificial neural networks
- sparse data
- graph mining
- test set
- sparse representation
- neural nets
- fuzzy logic
- training examples
- weighted graph
- recurrent networks
- training set
- feature space
- neural network structure
- training data
- social networks
- signal recovery
- self organizing maps