Differentially private matrix factorization with sub-linear convergence rate for personalized recommendation

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).

• Decentralized Matrix Factorization with Heterogeneous Differential Privacy (2022)73% match
• Privacy-Preserving Matrix Factorization for Recommendation Systems using Gaussian Mechanism (2023)73% match
• Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization (2025)72% match
• Scalable Recommendation with Poisson Factorization (2013)68% match
• PrivMVMF: Privacy-Preserving Multi-View Matrix Factorization for Recommender Systems (2022)67% match
• Federating Recommendations Using Differentially Private Prototypes (2020)67% match
• Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation (2024)67% match
• Metric Factorization: Recommendation beyond Matrix Factorization (2018)67% match