An Auxiliary Learning Task-Enhanced Graph Convolutional Network Model for Highly-accurate Node Classification on Weakly Supervised Graphs.
Zengmei ZhuoXin LuoMengChu ZhouPublished in: SMDS (2021)
Keyphrases
- weakly supervised
- network model
- highly accurate
- graph structure
- deep learning
- weakly supervised learning
- fully supervised
- superpixels
- directed graph
- supervised learning
- learning algorithm
- object class
- unsupervised learning
- support vector machine
- accurate models
- topic models
- degree distribution
- feature vectors
- graph theory
- viewpoint
- feature extraction
- semi supervised
- active learning
- named entities
- relation extraction
- neural network
- text classification
- image segmentation
- machine learning