Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity.
Mucong DingTahseen RabbaniBang AnEvan WangFurong HuangPublished in: NeurIPS (2022)
Keyphrases
- neural network
- training process
- training algorithm
- space complexity
- feed forward neural networks
- feedforward neural networks
- pattern recognition
- multi layer perceptron
- multi layer
- neural network training
- graph theory
- random walk
- graph structure
- artificial neural networks
- graph model
- genetic algorithm
- neural network structure
- primal sketch
- bipartite graph
- back propagation
- error back propagation
- computational complexity
- neural network model
- directed graph
- connected components
- training set
- graph mining
- sketch recognition
- fuzzy logic
- neural nets
- worst case
- training examples
- backpropagation algorithm
- recurrent networks
- supervised learning
- graph representation
- spanning tree
- self organizing maps
- decision problems
- graph matching
- recurrent neural networks