10 citations · 28 across the 6 of their papers we have counts for
6 papers
A Secure and Efficient Federated Learning Framework for NLP
Jieren Deng, Chenghong Wang, Xianrui Meng +7
In this work, we consider the problem of designing secure and efficient federated learning (FL) frameworks. Existing solutions either involve a trusted aggregator or require heavyw…
Privacy-Preserving XGBoost Inference
Xianrui Meng, Joan Feigenbaum
Although machine learning (ML) is widely used for predictive tasks, there are important scenarios in which ML cannot be used or at least cannot achieve its full potential. A major…
SAPAG: A Self-Adaptive Privacy Attack From Gradients
Yijue Wang, Jieren Deng, Dan Guo +5
Distributed learning such as federated learning or collaborative learning enables model training on decentralized data from users and only collects local gradients, where data is p…
Private Hierarchical Clustering and Efficient Approximation
Xianrui Meng, Dimitrios Papadopoulos, Alina Oprea +1
In collaborative learning, multiple parties contribute their datasets to jointly deduce global machine learning models for numerous predictive tasks. Despite its efficacy, this lea…
NED: An Inter-Graph Node Metric Based On Edit Distance
Haohan Zhu, Xianrui Meng, George Kollios
Node similarity is a fundamental problem in graph analytics. However, node similarity between nodes in different graphs (inter-graph nodes) has not received a lot of attention yet.…
Top-k Query Processing on Encrypted Databases with Strong Security Guarantees
Xianrui Meng, Haohan Zhu, George Kollios
Privacy concerns in outsourced cloud databases have become more and more important recently and many efficient and scalable query processing methods over encrypted data have been p…