knowledge graph learning 1risk bounds 1supervised learning 1theoretical analysis 1unsupervised pretraining 1
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math.ST2026
Toward a Unified Statistical Theory of Unsupervised Pretraining and Supervised Neural Knowledge Graph Learning
Jifan Zhang, Miklos Racz, Suqi Liu
The paper proposes a theoretically grounded two-stage framework that first unsupervisedly pretrains on heterogeneous data and then performs supervised learning for knowledge graph…
math.ST2024
Harnessing Multiple Correlated Networks for Exact Community Recovery
Miklós Z. Rácz, Jifan Zhang
We study the problem of learning latent community structure from multiple correlated networks, focusing on edge-correlated stochastic block models with two balanced communities. Re…