Adversarial learning on heterogeneous information networks

• Main Authors: HU, Binbin, FANG, Yuan, SHI, Chuan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Heterogeneous Information Network; Network Embedding; Generative Adversarial Network; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/4433; https://ink.library.smu.edu.sg/context/sis_research/article/5436/viewcontent/Adversarial_Learning_Heterogeneous_Information_Networks_pv.pdf
• Institution: Singapore Management University

Network embedding, which aims to represent network data in alow-dimensional space, has been commonly adopted for analyzingheterogeneous information networks (HIN). Although exiting HINembedding methods have achieved performance improvement tosome extent, they still face a few major weaknesses. Most...