X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation.
Guoliang HeSean ParkerEiko YonekiPublished in: MLSys (2023)
Keyphrases
- neural network
- reinforcement learning
- graph properties
- graph mining
- graph databases
- labeled graphs
- graph structures
- subgraph mining
- graph data
- graph theory
- directed graph
- random walk
- maximum clique
- function approximation
- function approximators
- state space
- frequent subgraph mining
- subgraph isomorphism
- connected subgraphs
- multi agent
- graph model
- weighted graph
- structured data
- reachability queries
- pattern recognition
- quasi cliques
- graph patterns
- frequent subgraphs
- topological information
- query graph
- subgraph matching
- optimal policy
- pattern mining
- fuzzy logic
- machine learning
- back propagation
- connected components
- dynamic programming
- graph matching
- graph search
- transformation rules
- graph structure
- graph kernels
- optimal control
- learning capabilities
- reinforcement learning algorithms
- dense subgraphs
- artificial neural networks
- data structure
- learning process
- neural network is trained
- neural network model
- markov decision processes
- radial basis function
- spanning tree
- bipartite graph
- edge weights
- temporal difference
- biological networks
- model free