GIST: Distributed Training for Large-Scale Graph Convolutional Networks.
Cameron R. WolfeJingkang YangArindam ChowdhuryChen DunArtun BayerSantiago SegarraAnastasios KyrillidisPublished in: CoRR (2021)
Keyphrases
- peer to peer networks
- computer networks
- distributed environment
- random walk
- structured peer to peer
- social networks
- heterogeneous networks
- small scale
- fully connected
- restricted boltzmann machine
- network nodes
- distributed systems
- peer to peer
- high scalability
- average degree
- massive graphs
- wide area network
- data intensive
- graph representation
- communication cost
- structured data
- weighted graph
- graph structure
- graph theory
- cooperative
- directed graph
- random graphs
- mobile agents
- recurrent networks
- training set
- community discovery
- graph structures
- supervised learning
- bipartite graph
- graph mining algorithms
- spanning tree
- graph mining
- echo state networks
- overlapping communities
- directed edges
- multi agent
- distributed stream processing
- network analysis
- betweenness centrality
- complex networks
- network size
- deep learning
- small world
- directed acyclic graph
- training process