211 citations · 1.4k across the 61 of their papers we have counts for
5 papers · 1 filter
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy
Ergute Bao, Yizheng Zhu, Xiaokui Xiao +4
Deep neural networks have strong capabilities of memorizing the underlying training data, which can be a serious privacy concern. An effective solution to this problem is to train…
GlassDB: An Efficient Verifiable Ledger Database System Through Transparency
Cong Yue, Tien Tuan Anh Dinh, Zhongle Xie +4
Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs --…
The Metaverse Data Deluge: What Can We Do About It?
Beng Chin Ooi, Gang Chen, Mike Zheng Shou +5
In the Metaverse, the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space…
Blockchain Goes Green? Part II: Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge
Dumitrel Loghin, Tien Tuan Anh Dinh, Aung Maw +3
While state-of-the-art permissioned blockchains can achieve thousands of transactions per second on commodity hardware with x86/64 architecture, their performance when running on d…
BoostMIS: Boosting Medical Image Semi-supervised Learning with Adaptive Pseudo Labeling and Informative Active Annotation
Wenqiao Zhang, Lei Zhu, James Hallinan +4
In this paper, we propose a novel semi-supervised learning (SSL) framework named BoostMIS that combines adaptive pseudo labeling and informative active annotation to unleash the po…