Mixture-Model-Based Graph for Privacy-Preserving Semi-Supervised Learning.
IEEE Access(2020)
Abstract
Privacy has become a major concern in data mining as it is utilized in many important applications. Distributed privacy-preserving data mining (DPPDM) is one of the techniques to address this concern, which focuses on protecting private information of members in distributed systems during data mining. As DPPDM is widely discussed in recent works, the semi-supervised manner of learning still draws ...
MoreTranslated text
Key words
Data privacy,Semisupervised learning,Task analysis,Data models,Mixture models,Clustering algorithms
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined