45 citations · 95 across the 6 of their papers we have counts for
6 papers
MC-GEN:Multi-level Clustering for Private Synthetic Data Generation
Mingchen Li, Di Zhuang, J. Morris Chang
With the development of machine learning and data science, data sharing is very common between companies and research institutes to avoid data scarcity. However, sharing original d…
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation
Di Zhuang, Mingchen Li, J. Morris Chang
Deep learning often requires a large amount of data. In real-world applications, e.g., healthcare applications, the data collected by a single organization (e.g., hospital) is ofte…
ESAI: Efficient Split Artificial Intelligence via Early Exiting Using Neural Architecture Search
Behnam Zeinali, Di Zhuang, J. Morris Chang
Recently, deep neural networks have been outperforming conventional machine learning algorithms in many computer vision-related tasks. However, it is not computationally acceptable…
Utility-aware Privacy-preserving Data Releasing
Di Zhuang, J. Morris Chang
In the big data era, more and more cloud-based data-driven applications are developed that leverage individual data to provide certain valuable services (the utilities). On the oth…
AutoGAN-based Dimension Reduction for Privacy Preservation
Hung Nguyen, Di Zhuang, Pei-Yuan Wu +1
Protecting sensitive information against data exploiting attacks is an emerging research area in data mining. Over the past, several different methods have been introduced to prote…
Enhanced PeerHunter: Detecting Peer-to-peer Botnets through Network-Flow Level Community Behavior Analysis
Di Zhuang, J. Morris Chang
Peer-to-peer (P2P) botnets have become one of the major threats in network security for serving as the fundamental infrastructure for various cyber-crimes. More challenges are invo…