On Sparse Linear Regression in the Local Differential Privacy Model

Author:

Wang DiORCID,Xu JinhuiORCID

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Library and Information Sciences,Computer Science Applications,Information Systems

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient Sparse Least Absolute Deviation Regression With Differential Privacy;IEEE Transactions on Information Forensics and Security;2024

2. Dynamic routing algorithm to normalize the routers utilization in mesh based NoC;2023 11th International Symposium on Electronic Systems Devices and Computing (ESDC);2023-05-04

3. Privacy of Synthetic Data: A Statistical Framework;IEEE Transactions on Information Theory;2023-01

4. High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data;Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems;2022-06-12

5. LDPCD: A Novel Method for Locally Differentially Private Community Detection;Computational Intelligence and Neuroscience;2022-01-10

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