Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks.
Mahdi MohammadizadehArash MozhdehiYani IoannouXin WangPublished in: CoRR (2024)
Keyphrases
- synthetic data
- neural network
- graph representation
- prior knowledge
- data sets
- missing values
- test data
- input data
- statistical methods
- pairwise
- noisy data
- data analysis
- knowledge discovery
- similarity measure
- training samples
- original data
- spectral graph
- database
- hierarchical data structure
- missing data
- data sources
- preprocessing
- training data
- high dimensional data
- data mining techniques
- directed graph
- graph structure
- weighted graph
- training process
- similarity matrix
- loss minimization
- decision trees
- learning algorithm