Federated Matrix Factorization with Privacy Guarantee
Summary: Unifies matrix factorization across vertical, horizontal, and local federated learning with convergence guarantees and end-to-end privacy analysis. Embedding clipping provides differential privacy, while secure aggregation substantially improves local-FL utility over local DP. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zitao Li (Purdue University)
- 2. Bolin Ding (Alibaba)
- 3. Ce Zhang (ETH Zurich)
- 4. Ninghui Li (Purdue University)
- 5. Jingren Zhou (Alibaba)
BibTeX Citation
@article{li_vldb22,
title = {{Federated Matrix Factorization with Privacy Guarantee}},
author = {Li, Zitao and Ding, Bolin and Zhang, Ce and Li, Ninghui and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {4},
pages = {900--913},
doi = {10.14778/3503585.3503598},
url = {https://doi.org/10.14778/3503585.3503598},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,353 | Differentially Private Vertical Federated Clustering | 2023 | VLDB | 5.9042628e-05 |
| 6,421 | Falcon: A Privacy-Preserving and Interpretable Vertical Federated Learning System | 2023 | VLDB | 5.8819368e-05 |
| 8,814 | FederatedScope: A Flexible Federated Learning Platform for Heterogeneity | 2023 | VLDB | 5.3647251e-05 |
| 9,473 | FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data | 2023 | SIGMOD | 5.2634238e-05 |
| 10,934 | PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning | 2025 | VLDB | 5.093636e-05 |
| 11,191 | A Profit-Maximizing Data Marketplace with Differentially Private Federated Learning under Price Competition | 2024 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 62 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00038970535 |
| 123 | Revealing Information while Preserving Privacy | 2003 | PODS | 0.00031082693 |
| 1,249 | Privacy Preserving Vertical Federated Learning for Tree-based Models | 2020 | VLDB | 0.00011495357 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,934 | PS-MI: Accurate, Efficient, and Private Data Valuation in Vertical Federated Learning | 2025 | VLDB |
| 2 | 7,833 | An Introduction to Federated Computation | 2022 | SIGMOD |
| 3 | 8,045 | Contributions Estimation in Federated Learning: A Comprehensive Experimental Evaluation | 2024 | VLDB |
| 4 | 1,249 | Privacy Preserving Vertical Federated Learning for Tree-based Models | 2020 | VLDB |
| 5 | 5,746 | Federated Heavy Hitter Analytics with Local Differential Privacy | 2025 | SIGMOD |
| 6 | 3,237 | BlindFL: Vertical Federated Machine Learning without Peeking into Your Data | 2022 | SIGMOD |
| 7 | 11,252 | Uldp-FL: Federated Learning with Across-Silo User-Level Differential Privacy | 2024 | VLDB |
| 8 | 4,446 | Projected Federated Averaging with Heterogeneous Differential Privacy | 2022 | VLDB |
| 9 | 6,353 | Differentially Private Vertical Federated Clustering | 2023 | VLDB |
| 10 | 10,387 | P2 FedRec: Towards Privacy-Preserving and Personalized Federated Recommendation via Relationship Awareness | 2026 | SIGMOD |