11 citations · 25 across the 5 of their papers we have counts for
5 papers
Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropy
Jiaren Xiao, Quanyu Dai, Xiao Shen +4
Label scarcity in a graph is frequently encountered in real-world applications due to the high cost of data labeling. To this end, semi-supervised domain adaptation (SSDA) on graph…
Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization
Qijiong Liu, Lu Fan, Jiaren Xiao +2
Category information plays a crucial role in enhancing the quality and personalization of recommender systems. Nevertheless, the availability of item category information is not co…
A Survey about application based on RF signals
Jiaren Xiao
With the popularity of commercial wireless devices, the research based on RF signal has developed rapidly in the past decade. RF signals have great advantages in environmental perc…
Adversarially Regularized Graph Attention Networks for Inductive Learning on Partially Labeled Graphs
Jiaren Xiao, Quanyu Dai, Xiaochen Xie +2
The high cost of data labeling often results in node label shortage in real applications. To improve node classification accuracy, graph-based semi-supervised learning leverages th…
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
Quanyu Dai, Xiao-Ming Wu, Jiaren Xiao +2
This paper studies the problem of cross-network node classification to overcome the insufficiency of labeled data in a single network. It aims to leverage the label information in…