72 citations · 197 across the 19 of their papers we have counts for
4 papers · 1 filter
SEAL: Semi-supervised Adversarial Active Learning on Attributed Graphs
Yayong Li, Jie Yin, Ling Chen
Active learning (AL) on attributed graphs has received increasing attention with the prevalence of graph-structured data. Although AL has been widely studied for alleviating label…
Latent Adversarial Defence with Boundary-guided Generation
Xiaowei Zhou, Ivor W. Tsang, Jie Yin
Deep Neural Networks (DNNs) have recently achieved great success in many tasks, which encourages DNNs to be widely used as a machine learning service in model sharing scenarios. Ho…
Search Efficient Binary Network Embedding
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Traditional network embedding primarily focuses on learning a continuous vector representation for each node, preserving network structure and/or node content information, such tha…
Attributed Network Embedding via Subspace Discovery
Daokun Zhang, Jie Yin, Xingquan Zhu +1
Network embedding aims to learn a latent, low-dimensional vector representations of network nodes, effective in supporting various network analytic tasks. While prior arts on netwo…