A Structural-Clustering Based Active Learning for Graph Neural Networks.
Ricky Maulana FajriYulong PeiLu YinMykola PechenizkiyPublished in: IDA (1) (2024)
Keyphrases
- active learning
- neural network
- graph representation
- pattern recognition
- structural information
- machine learning
- graph structure
- graph model
- random walk
- structured data
- directed graph
- graph theory
- learning strategies
- artificial neural networks
- semi supervised
- structural patterns
- random sampling
- weighted graph
- fuzzy logic
- supervised learning
- neural network model
- feed forward
- connected components
- multi layer
- spanning tree
- back propagation
- graph matching
- recurrent neural networks
- neural nets
- data sets
- self organizing maps
- labeled data
- graph databases
- training data
- selective sampling