Graph Filters for Signal Processing and Machine Learning on Graphs.
Elvin IsufiFernando GamaDavid I. ShumanSantiago SegarraPublished in: CoRR (2022)
Keyphrases
- signal processing
- machine learning
- pattern recognition
- graph matching
- graph representation
- graph theory
- graph structure
- weighted graph
- directed graph
- graph databases
- graph mining
- labeled graphs
- structural pattern recognition
- graph classification
- graph theoretic
- graph structures
- graph construction
- graph properties
- graph theoretical
- graph model
- random graphs
- graph representations
- adjacency matrix
- graph partitioning
- bipartite graph
- graph data
- graph search
- image processing
- spanning tree
- graph clustering
- series parallel
- undirected graph
- graph kernels
- maximum cardinality
- connected dominating set
- dynamic graph
- neighborhood graph
- graph isomorphism
- evolving graphs
- computer vision
- subgraph isomorphism
- graph transformation
- reachability queries
- dense subgraphs
- real world graphs
- fourier transform
- social graphs
- random walk
- graph drawing
- graph patterns
- connected graphs
- inexact graph matching
- maximum common subgraph
- adjacency graph
- community discovery
- query graph
- small world
- structured data
- maximum clique
- massive graphs
- directed acyclic
- edge weights
- topological information
- minimum spanning tree
- spam filters
- graph embedding
- bounded treewidth
- web graph
- connected components
- maximal cliques
- finding the shortest path
- data mining
- graph layout
- semi supervised learning
- planar graphs
- polynomial time complexity