3 papers
cs.LG2025
Enhancing Contrastive Link Prediction With Edge Balancing Augmentation
Chen-Hao Chang, Hui-Ju Hung, Chia-Hsun Lu +1
Link prediction is one of the most fundamental tasks in graph mining, which motivates the recent studies of leveraging contrastive learning to enhance the performance. However, we…
cs.LG2025
Watermarking Kolmogorov-Arnold Networks for Emerging Networked Applications via Activation Perturbation
Chia-Hsun Lu, Guan-Jhih Wu, Ya-Chi Ho +1
With the increasing importance of protecting intellectual property in machine learning, watermarking techniques have gained significant attention. As advanced models are increasing…
cs.LG2025
Transferring Social Network Knowledge from Multiple GNN Teachers to Kolmogorov-Arnold Networks
Yuan-Hung Chao, Chia-Hsun Lu, Chih-Ya Shen
Graph Neural Networks (GNNs) have shown strong performance on graph-structured data, but their reliance on graph connectivity often limits scalability and efficiency. Kolmogorov-Ar…