A Graph Learning Algorithm Based On Gaussian Markov Random Fields And Minimax Concave Penalty.
Tatsuya KoyakumaruMasahiro YukawaEduardo PavezAntonio OrtegaPublished in: ICASSP (2021)
Keyphrases
- learning algorithm
- gaussian markov random fields
- objective function
- directed graph
- random walk
- machine learning
- graph representation
- graph structure
- reinforcement learning
- supervised learning
- active learning
- weighted graph
- graph theory
- back propagation
- learning problems
- machine learning algorithms
- training examples
- directed acyclic graph
- graph model
- spanning tree
- learning scheme
- computationally efficient
- training data
- structured data
- learning process
- graph matching
- search space
- graph mining