Solving Recurrent MIPs with Semi-supervised Graph Neural Networks.
Konstantinos BenidisUgo RosoliaSyama RangapuramGeorge IosifidisGeorgios S. PaschosPublished in: CoRR (2023)
Keyphrases
- semi supervised
- neural network
- semi supervised classification
- graph construction
- recurrent neural networks
- feed forward
- label propagation
- semi supervised learning
- random walk
- graph based semi supervised learning
- pattern recognition
- graph theory
- training process
- structured data
- manifold learning
- directed graph
- self organizing maps
- semi supervised clustering
- back propagation
- artificial neural networks
- labeled data
- unsupervised learning
- multi view
- supervised learning
- graph databases
- genetic algorithm
- weighted graph
- graph structure
- pairwise
- active learning
- clustering algorithm
- graph embedding
- graph model
- clustering method
- graph representation
- fuzzy logic
- subspace learning
- series parallel
- constrained clustering
- unlabeled data
- neural nets
- graph theoretic
- combinatorial optimization
- neural network model
- graph matching