33 citations · 60 across the 5 of their papers we have counts for
5 papers
SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network
Ziang Zhou, Jieming Shi, Renchi Yang +2
Heterogeneous graphs are ubiquitous to model complex data. There are urgent needs on powerful heterogeneous graph neural networks to effectively support important applications. We…
Detecting Escalation Level from Speech with Transfer Learning and Acoustic-Lexical Information Fusion
Ziang Zhou, Yanze Xu, Ming Li
Textual escalation detection has been widely applied to e-commerce companies' customer service systems to pre-alert and prevent potential conflicts. Similarly, in public areas such…
SCE: Scalable Network Embedding from Sparsest Cut
Shengzhong Zhang, Zengfeng Huang, Haicang Zhou +1
Large-scale network embedding is to learn a latent representation for each node in an unsupervised manner, which captures inherent properties and structural information of the unde…
Multi-consensus Decentralized Accelerated Gradient Descent
Haishan Ye, Luo Luo, Ziang Zhou +1
This paper considers the decentralized convex optimization problem, which has a wide range of applications in large-scale machine learning, sensor networks, and control theory. We…
Effective Stabilized Self-Training on Few-Labeled Graph Data
Ziang Zhou, Jieming Shi, Shengzhong Zhang +2
Graph neural networks (GNNs) are designed for semi-supervised node classification on graphs where only a subset of nodes have class labels. However, under extreme cases when very f…