5 papers
Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation
Pengcheng Xu, Boyu Wang, Charles Ling
Current methods of blended targets domain adaptation (BTDA) usually infer or consider domain label information but underemphasize hybrid categorical feature structures of targets,…
Graph Domain Adaptation via Homophily-Agnostic Reconstructing Structure
Ruiyi Fang, Shuo Wang, Ruizhi Pu +8
Graph Domain Adaptation (GDA) transfers knowledge from labeled source graphs to unlabeled target graphs, addressing the challenge of label scarcity. However, existing GDA methods t…
Homophily Enhanced Graph Domain Adaptation
Ruiyi Fang, Bingheng Li, Jingyu Zhao +5
Graph Domain Adaptation (GDA) transfers knowledge from labeled source graphs to unlabeled target graphs, addressing the challenge of label scarcity. In this paper, we highlight the…
ZETA: Leveraging Z-order Curves for Efficient Top-k Attention
Qiuhao Zeng, Jerry Huang, Peng Lu +4
Over recent years, the Transformer has become a fundamental building block for sequence modeling architectures. Yet at its core is the use of self-attention, whose memory and compu…
On the Benefits of Attribute-Driven Graph Domain Adaptation
Ruiyi Fang, Bingheng Li, Zhao Kang +5
Graph Domain Adaptation (GDA) addresses a pressing challenge in cross-network learning, particularly pertinent due to the absence of labeled data in real-world graph datasets. Rece…