919 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Central China Normal UniversityCN652 papers
- University of Science and Technology of ChinaCN646 papers
- Tsinghua UniversityCN642 papers
- Peking UniversityCN633 papers
- Shandong UniversityCN628 papers
- Zhejiang UniversityCN612 papers
- Nanjing Normal UniversityCN611 papers
- Hunan UniversityCN608 papers
- Henan Normal UniversityCN607 papers
- Sichuan UniversityCN607 papers
- China Center of Advanced Science and TechnologyCN604 papers
- Nankai UniversityCN604 papers
9 papers · 1 filter
Adaptive NN graph model
Jiaye Li, Hang Xu, Shichao Zhang
The -nearest neighbors (NN) algorithm is a cornerstone of non-parametric classification in artificial intelligence, yet its deployment in large-scale applications is persiste…
Shrinkage Initialization for Smooth Learning of Neural Networks
Miao Cheng, Feiyan Zhou, Hongwei Zou +1
The successes of intelligent systems have quite relied on the artificial learning of information, which lead to the broad applications of neural learning solutions. As a common sen…
Graph Size-imbalanced Learning with Energy-guided Structural Smoothing
Jiawen Qin, Pengfeng Huang, Qingyun Sun +3
Graph is a prevalent data structure employed to represent the relationships between entities, frequently serving as a tool to depict and simulate numerous systems, such as molecule…
Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation
Chengyu Li, Debo Cheng, Guixian Zhang +2
Graph Neural Networks (GNNs) have demonstrated strong performance in graph representation learning across various real-world applications. However, they often produce biased predic…
Leaning Time-Varying Instruments for Identifying Causal Effects in Time-Series Data
Debo Cheng, Ziqi Xu, Jiuyong Li +4
Querying causal effects from time-series data is important across various fields, including healthcare, economics, climate science, and epidemiology. However, this task becomes com…
BRFL: A Blockchain-based Byzantine-Robust Federated Learning Model
Yang Li, Chunhe Xia, Chang Li +1
With the increasing importance of machine learning, the privacy and security of training data have become critical. Federated learning, which stores data in distributed nodes and s…
Hyperbolic Geometric Graph Representation Learning for Hierarchy-imbalance Node Classification
Xingcheng Fu, Yuecen Wei, Qingyun Sun +4
Learning unbiased node representations for imbalanced samples in the graph has become a more remarkable and important topic. For the graph, a significant challenge is that the topo…
FLBench: A Benchmark Suite for Federated Learning
Yuan Liang, Yange Guo, Yanxia Gong +3
Federated learning is a new machine learning paradigm. The goal is to build a machine learning model from the data sets distributed on multiple devices so-called an isolated data i…
ServeNet: A Deep Neural Network for Web Services Classification
Yilong Yang, Nafees Qamar, Peng Liu +4
Automated service classification plays a crucial role in service discovery, selection, and composition. Machine learning has been widely used for service classification in recent y…