211 citations · 1.4k across the 61 of their papers we have counts for
8 papers · 1 filter
Communication-efficient Decentralized Machine Learning over Heterogeneous Networks
Pan Zhou, Qian Lin, Dumitrel Loghin +3
In the last few years, distributed machine learning has been usually executed over heterogeneous networks such as a local area network within a multi-tenant cluster or a wide area…
MLCask: Efficient Management of Component Evolution in Collaborative Data Analytics Pipelines
Zhaojing Luo, Sai Ho Yeung, Meihui Zhang +7
With the ever-increasing adoption of machine learning for data analytics, maintaining a machine learning pipeline is becoming more complex as both the datasets and trained models e…
Feature Inference Attack on Model Predictions in Vertical Federated Learning
Xinjian Luo, Yuncheng Wu, Xiaokui Xiao +1
Federated learning (FL) is an emerging paradigm for facilitating multiple organizations' data collaboration without revealing their private data to each other. Recently, vertical F…
Privacy Preserving Vertical Federated Learning for Tree-based Models
Yuncheng Wu, Shaofeng Cai, Xiaokui Xiao +2
Federated learning (FL) is an emerging paradigm that enables multiple organizations to jointly train a model without revealing their private data to each other. This paper studies…
ForkBase: Immutable, Tamper-evident Storage Substrate for Branchable Applications
Qian Lin, Kaiyuan Yang, Tien Tuan Anh Dinh +8
Data collaboration activities typically require systematic or protocol-based coordination to be scalable. Git, an effective enabler for collaborative coding, has been attested for…
TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications
Kaiping Zheng, Shaofeng Cai, Horng Ruey Chua +3
In high stakes applications such as healthcare and finance analytics, the interpretability of predictive models is required and necessary for domain practitioners to trust the pred…