Modularity Optimization as a Training Criterion for Graph Neural Networks.
Tsuyoshi MurataNaveed AfzalPublished in: CoRR (2022)
Keyphrases
- neural network
- training process
- training algorithm
- multi layer perceptron
- feed forward neural networks
- error back propagation
- training set
- multi layer
- genetic algorithm
- neural network training
- backpropagation algorithm
- feedforward neural networks
- graph representation
- optimization algorithm
- graph model
- pattern recognition
- neural network structure
- weighted graph
- optimization problems
- artificial neural networks
- optimization method
- normalized cut
- supervised learning
- stochastic gradient descent
- back propagation
- recurrent networks
- fuzzy logic
- directed graph
- global optimization
- highly non linear
- graph theory
- knn
- radial basis function network
- feature selection
- minimum classification error
- random walk
- graph theoretic
- recurrent neural networks
- training phase
- fuzzy neural network
- directed acyclic graph
- neural network model
- graph matching
- bipartite graph
- neural nets