50 citations · 120 across the 8 of their papers we have counts for
8 papers
Efficient Densest Flow Queries in Transaction Flow Networks (Complete Version)
Jiaxin Jiang, Yunxiang Zhao, Lyu Xu +4
Transaction flow networks are crucial in detecting illicit activities such as wash trading, credit card fraud, cashback arbitrage fraud, and money laundering. \revise{Our collabora…
DaMSTF: Domain Adversarial Learning Enhanced Meta Self-Training for Domain Adaptation
Menglong Lu, Zhen Huang, Yunxiang Zhao +3
Self-training emerges as an important research line on domain adaptation. By taking the model's prediction as the pseudo labels of the unlabeled data, self-training bootstraps the…
Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification
Menglong Lu, Zhen Huang, Zhiliang Tian +3
Text classification is a fundamental task for natural language processing, and adapting text classification models across domains has broad applications. Self-training generates ps…
Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems
Yixin Su, Yunxiang Zhao, Sarah Erfani +2
Detecting beneficial feature interactions is essential in recommender systems, and existing approaches achieve this by examining all the possible feature interactions. However, the…
Graph Pooling via Coarsened Graph Infomax
Yunsheng Pang, Yunxiang Zhao, Dongsheng Li
Graph pooling that summaries the information in a large graph into a compact form is essential in hierarchical graph representation learning. Existing graph pooling methods either…
WGCN: Graph Convolutional Networks with Weighted Structural Features
Yunxiang Zhao, Jianzhong Qi, Qingwei Liu +1
Graph structural information such as topologies or connectivities provides valuable guidance for graph convolutional networks (GCNs) to learn nodes' representations. Existing GCN m…
HexCNN: A Framework for Native Hexagonal Convolutional Neural Networks
Yunxiang Zhao, Qiuhong Ke, Flip Korn +2
Hexagonal CNN models have shown superior performance in applications such as IACT data analysis and aerial scene classification due to their better rotation symmetry and reduced an…
CBHE: Corner-based Building Height Estimation for Complex Street Scene Images
Yunxiang Zhao, Jianzhong Qi, Rui Zhang
Building height estimation is important in many applications such as 3D city reconstruction, urban planning, and navigation. Recently, a new building height estimation method using…