3 papers
cs.LG2019
Learning Graph Embedding with Adversarial Training Methods
Shirui Pan, Ruiqi Hu, Sai-fu Fung +3
Graph embedding aims to transfer a graph into vectors to facilitate subsequent graph analytics tasks like link prediction and graph clustering. Most approaches on graph embedding f…
cs.SI2018
Universal Network Representation for Heterogeneous Information Networks
Ruiqi Hu, Celina Ping Yu, Sai-Fu Fung +3
Network representation aims to represent the nodes in a network as continuous and compact vectors, and has attracted much attention in recent years due to its ability to capture co…
cs.CR2018
Privacy-preserving Stochastic Gradual Learning
Bo Han, Ivor W. Tsang, Xiaokui Xiao +3
It is challenging for stochastic optimizations to handle large-scale sensitive data safely. Recently, Duchi et al. proposed private sampling strategy to solve privacy leakage in st…