4 papers
Measuring Graph-to-Graph Semantic Similarity in Knowledge Graphs: An Empirical Evaluation of Knowledge Graph Embeddings
Seungryeol Baek, Wooseok Sim, Hogun Park
A Knowledge Graph (KG) represents facts as structured triples and is widely used to organize relational knowledge across diverse domains. Just as textual information ranges from wo…
Low-pass Personalized Subgraph Federated Recommendation
Wooseok Sim, Hogun Park
Federated Recommender Systems (FRS) preserve privacy by training decentralized models on client-specific user-item subgraphs without sharing raw data. However, FRS faces a unique c…
Federated Recommender System with Data Valuation for E-commerce Platform
Jongwon Park, Minku Kang, Wooseok Sim +2
Federated Learning (FL) is gaining prominence in machine learning as privacy concerns grow. This paradigm allows each client (e.g., an individual online store) to train a recommend…
Curriculum Guided Personalized Subgraph Federated Learning
Minku Kang, Hogun Park
Subgraph Federated Learning (FL) aims to train Graph Neural Networks (GNNs) across distributed private subgraphs, but it suffers from severe data heterogeneity. To mitigate data he…