AI RESEARCH
Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases
arXiv CS.LG
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ArXi:2603.07916v1 Announce Type: cross In recent advances, to enable a fully data-driven learning paradigm on relational databases (RDB), relational deep learning (RDL) is proposed to structure the RDB as a heterogeneous entity graph and adopt the graph neural network (GNN) as the predictive model. However, existing RDL methods neglect the imbalance problem of relational data in RDBs and risk under-representing the minority entities, leading to an unusable model in practice.