7 citations · 11 across the 6 of their papers we have counts for
6 papers
iDML: Incentivized Decentralized Machine Learning
Haoxiang Yu, Hsiao-Yuan Chen, Sangsu Lee +3
With the rising emergence of decentralized and opportunistic approaches to machine learning, end devices are increasingly tasked with training deep learning models on-devices using…
Optimizing Video Caching at the Edge: A Hybrid Multi-Point Process Approach
Xianzhi Zhang, Yipeng Zhou, Di Wu +4
It is always a challenging problem to deliver a huge volume of videos over the Internet. To meet the high bandwidth and stringent playback demand, one feasible solution is to cache…
Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated Learning
Wenzhuo Yang, Yipeng Zhou, Maio Hu +4
Federated Learning (FL) is an emerging paradigm through which decentralized devices can collaboratively train a common model. However, a serious concern is the leakage of privacy f…
A Privacy-Preserving Data Inference Framework for Internet of Health Things Networks
James Jin Kang, Mahdi Dibaei, Gang Luo +2
Privacy protection in electronic healthcare applications is an important consideration due to the sensitive nature of personal health data. Internet of Health Things (IoHT) network…
An ensemble learning approach for software semantic clone detection
Min Fu, Gang Luo, Xi Zheng +3
Code clone is a serious problem in software and has the potential to software defects, maintenance overhead, and licensing violations. Therefore, clone detection is important for r…
Our Practice Of Using Machine Learning To Recognize Species By Voice
Siddhardha Balemarthy, Atul Sajjanhar, James Xi Zheng
As the technology is advancing, audio recognition in machine learning is improved as well. Research in audio recognition has traditionally focused on speech. Living creatures (espe…