TypeBandit allocates a global sampling budget at the node-type level via bandits to supply type summaries as contextual signals for attribute completion, delivering dataset-dependent gains when plugged into standard heterogeneous GNNs like R-GCN and HGT.
Bandit samplers for training graph neural networks,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
TypeBandit: Type-Level Context Allocation and Reweighting for Effective Attribute Completion in Heterogeneous Graph Neural Networks
TypeBandit allocates a global sampling budget at the node-type level via bandits to supply type summaries as contextual signals for attribute completion, delivering dataset-dependent gains when plugged into standard heterogeneous GNNs like R-GCN and HGT.