Fast Differentially Private Matrix Factorization

1. 2022Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendationcited by 22
2. 2021Privately Publishable Per-instance Privacycited by 12
3. 2023Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendationscited by 12
4. 2021Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Ratescited by 10
5. 2023Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Modelscited by 7
6. 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpointcited by 5
7. 2023Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approachcited by 3
8. 2021Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computationcited by 2
9. 2021Private and Utility Enhanced Recommendations with Local Differential Privacy and Gaussian Mixture Modelcited by 2
10. 2022Privacy-preserving Non-negative Matrix Factorization with Outlierscited by 2
11. 2024Privacy-preserving recommender system using the data collaboration analysis for distributed datasetscited by 2
12. 2025Privacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender Systemscited by 2

1. 2026One-Sided Matrix Completion from Ultra-Sparse Samples18 Jan 2026
2. 2025Privacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender Systems27 Nov 2025
3. 2024Privacy-preserving recommender system using the data collaboration analysis for distributed datasets24 May 2024
4. 2024Near-Optimal differentially private low-rank trace regression with guaranteed private initialization24 Mar 2024
5. 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint28 Oct 2023
6. 2023Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach17 Sep 2023
7. 2023Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models8 Sep 2023
8. 2023Privacy-Preserving Matrix Factorization for Recommendation Systems using Gaussian Mechanism11 Apr 2023
9. 2023Fairness-aware Differentially Private Collaborative Filtering16 Mar 2023
10. 2023Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations13 Feb 2023
11. 2022Decentralized Matrix Factorization with Heterogeneous Differential Privacy1 Dec 2022
12. 2022Privacy-preserving Non-negative Matrix Factorization with Outliers2 Nov 2022

1. 2023Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendationscited by 12

1. 2023Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations13 Feb 2023

1. 2022Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendationcited by 22
2. 2021Privately Publishable Per-instance Privacycited by 12
3. 2021Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Ratescited by 10
4. 2023Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Modelscited by 7
5. 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpointcited by 5
6. 2023Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approachcited by 3
7. 2021Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computationcited by 2
8. 2021Private and Utility Enhanced Recommendations with Local Differential Privacy and Gaussian Mixture Modelcited by 2
9. 2022Privacy-preserving Non-negative Matrix Factorization with Outlierscited by 2
10. 2024Privacy-preserving recommender system using the data collaboration analysis for distributed datasetscited by 2
11. 2025Privacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender Systemscited by 2
12. 2023Fairness-aware Differentially Private Collaborative Filteringcited by 1

12 most cited of 19 · All 19 (JSON)

1. 2026One-Sided Matrix Completion from Ultra-Sparse Samples18 Jan 2026
2. 2025Privacy-Utility-Bias Trade-offs for Privacy-Preserving Recommender Systems27 Nov 2025
3. 2024Privacy-preserving recommender system using the data collaboration analysis for distributed datasets24 May 2024
4. 2024Near-Optimal differentially private low-rank trace regression with guaranteed private initialization24 Mar 2024
5. 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint28 Oct 2023
6. 2023Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach17 Sep 2023
7. 2023Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models8 Sep 2023
8. 2023Privacy-Preserving Matrix Factorization for Recommendation Systems using Gaussian Mechanism11 Apr 2023
9. 2023Fairness-aware Differentially Private Collaborative Filtering16 Mar 2023
10. 2022Decentralized Matrix Factorization with Heterogeneous Differential Privacy1 Dec 2022
11. 2022Privacy-preserving Non-negative Matrix Factorization with Outliers2 Nov 2022
12. 2022Introducing the Huber mechanism for differentially private low-rank matrix completion16 Jun 2022

12 newest of 19 · All 19 (JSON)