Differentially Private Sparse Mapping for Privacy-Preserving Cross Domain Recommendation-Reference-Cited by-同舟云学术

Differentially Private Sparse Mapping for Privacy-Preserving Cross Domain Recommendation

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
language:
Short-container-title:

Author:

Liu Weiming¹^ORCID,Zheng Xiaolin¹^ORCID,Chen Chaochao¹^ORCID,Hu Mengling¹^ORCID,Liao Xinting¹^ORCID,Wang Fan¹^ORCID,Tan Yanchao²^ORCID,Meng Dan³^ORCID,Wang Jun³^ORCID

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Fuzhou University, Fuzhou, China

3. OPPO Research Institute, Shenzhen, China

Funder

Leading Expert of ??Ten Thousands Talent Program?? of Zhejiang Province

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3611924

Reference76 articles.

1. Deep Learning with Differential Privacy

2. A survey of privacy solutions using blockchain for recommender systems: Current status, classification and open issues;Abduljabbar Tamara Abdulmunim;Comput. J.,2021

3. Luigi Ambrosio , Klaus Deckelnick , Gerhard Dziuk , Masayasu Mimura , Vsevolod A Solonnikov , Halil Mete Soner, and Luigi Ambrosio . 2003 . Lecture notes on optimal transport problems. Springer . Luigi Ambrosio, Klaus Deckelnick, Gerhard Dziuk, Masayasu Mimura, Vsevolod A Solonnikov, Halil Mete Soner, and Luigi Ambrosio. 2003. Lecture notes on optimal transport problems. Springer.

4. The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy

5. Mathieu Blondel , Vivien Seguy , and Antoine Rolet . 2018 . Smooth and sparse optimal transport . In International conference on artificial intelligence and statistics. PMLR, 880--889 . Mathieu Blondel, Vivien Seguy, and Antoine Rolet. 2018. Smooth and sparse optimal transport. In International conference on artificial intelligence and statistics. PMLR, 880--889.

Cited by 1 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. Privacy Preserving Multi-source Cross-domain Recommendation based on Knowledge Graph;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-01-05