41 citations · 47 across the 10 of their papers we have counts for
4 papers · 1 filter
NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications
Guangyi Xiao, Weiwei Xiang, Huan Liu +4
We propose a new general Graph Adversarial Domain Adaptation (GADA) based on semantic knowledge reasoning of class structure for solving the problem of unsupervised domain adaptati…
Recurrent Coupled Topic Modeling over Sequential Documents
Jinjin Guo, Longbing Cao, Zhiguo Gong
The abundant sequential documents such as online archival, social media and news feeds are streamingly updated, where each chunk of documents is incorporated with smoothly evolving…
Zero-shot Node Classification with Decomposed Graph Prototype Network
Zheng Wang, Jialong Wang, Yuchen Guo +1
Node classification is a central task in graph data analysis. Scarce or even no labeled data of emerging classes is a big challenge for existing methods. A natural question arises:…
Expanding Semantic Knowledge for Zero-shot Graph Embedding
Zheng Wang, Ruihang Shao, Changping Wang +3
Zero-shot graph embedding is a major challenge for supervised graph learning. Although a recent method RECT has shown promising performance, its working mechanisms are not clear an…