差分隐私论文趋势 2023–2026

DP 训练

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 479 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

差分隐私论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
20236721272117
20246125243113
20256629474146
20262331427103

代表论文

按年份和会议均匀挑选,方便快速看到每一届的样貌

全部差分隐私论文

共 146 篇,第 3 / 3 页

  1. NeurIPS 2025Differentially Private Relational Learning with Entity-level Privacy Guarantees
  2. NeurIPS 2025DIFFSSR: Stereo Image Super-resolution Using Differential Transformer
  3. NeurIPS 2025Discovering Symbolic Partial Differential Equation by Abductive Learning
  4. NeurIPS 2025Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data
  5. NeurIPS 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
  6. NeurIPS 2025GeoClip: Geometry-Aware Clipping for Differentially Private SGD
  7. NeurIPS 2025How Well Can Differential Privacy Be Audited in One Run?
  8. NeurIPS 2025Instance-Optimality for Private KL Distribution Estimation
  9. NeurIPS 2025Learning Differential Pyramid Representation for Tone Mapping
  10. NeurIPS 2025Locally Optimal Private Sampling: Beyond the Global Minimax
  11. NeurIPS 2025Mitigating the Privacy–Utility Trade-off in Decentralized Federated Learning via f-Differential Privacy
  12. NeurIPS 2025Multi-Class Support Vector Machine with Differential Privacy
  13. NeurIPS 2025Nearly-Linear Time Private Hypothesis Selection with the Optimal Approximation Factor
  14. NeurIPS 2025Neural Fractional Attention Differential Equations
  15. NeurIPS 2025On Traceability in $\ell_p$ Stochastic Convex Optimization
  16. NeurIPS 2025Online Locally Differentially Private Conformal Prediction via Binary Inquiries
  17. NeurIPS 2025Online robust locally differentially private learning for nonparametric regression
  18. NeurIPS 2025Optimal Best Arm Identification under Differential Privacy
  19. NeurIPS 2025Optimal Regret of Bandits under Differential Privacy
  20. NeurIPS 2025PREAMBLE: Private and Efficient Aggregation via Block Sparse Vectors
  21. NeurIPS 2025Privacy amplification by random allocation
  22. NeurIPS 2025Private Continual Counting of Unbounded Streams
  23. NeurIPS 2025Private Evolution Converges
  24. NeurIPS 2025Private Geometric Median in Nearly-Linear Time
  25. NeurIPS 2025Private Hyperparameter Tuning with Ex-Post Guarantee
  26. NeurIPS 2025Private Online Learning against an Adaptive Adversary: Realizable and Agnostic Settings
  27. NeurIPS 2025Private Set Union with Multiple Contributions
  28. NeurIPS 2025Private Statistical Estimation via Truncation
  29. NeurIPS 2025Private Training Large-scale Models with Efficient DP-SGD
  30. NeurIPS 2025Private Zeroth-Order Optimization with Public Data
  31. NeurIPS 2025Projective Equivariant Networks via Second-order Fundamental Differential Invariants
  32. NeurIPS 2025Purifying Approximate Differential Privacy with Randomized Post-processing
  33. NeurIPS 2025Query-Efficient Locally Private Hypothesis Selection via the Scheffe Graph
  34. NeurIPS 2025Sequentially Auditing Differential Privacy
  35. NeurIPS 2025Setting $\varepsilon$ is not the Issue in Differential Privacy
  36. NeurIPS 2025Sketched Gaussian Mechanism for Private Federated Learning
  37. NeurIPS 2025Solving Partial Differential Equations via Radon Neural Operator
  38. NeurIPS 2025Sum Estimation under Personalized Local Differential Privacy
  39. NeurIPS 2025Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries
  40. NeurIPS 2025The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
  41. NeurIPS 2025Tight Bounds for Answering Adaptively Chosen Concentrated Queries
  42. NeurIPS 2025Time-uniform and Asymptotic Confidence Sequence of Quantile under Local Differential Privacy
  43. NeurIPS 2025UEPI: Universal Energy-Behavior-Preserving Integrators for Energy Conservative/Dissipative Differential Equations
  44. NeurIPS 2025Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
  45. NeurIPS 2025Wavy Transformer
  46. NeurIPS 2025⁠When Data Can't Meet: Estimating Correlation Across Privacy Barriers

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查差分隐私在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "differential-privacy"}

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常见问题

2023–2026 年四大会议一共有多少篇差分隐私论文?
共 479 篇,按年份分别是 2023 年 117 篇、2024 年 113 篇、2025 年 146 篇、2026 年 103 篇。
NeurIPS 2026 有多少篇差分隐私论文?
NeurIPS 2026 有 23 篇差分隐私论文,上一届是 66 篇。
ICLR 2026 有多少篇差分隐私论文?
ICLR 2026 有 31 篇差分隐私论文,上一届是 29 篇。
ICML 2026 有多少篇差分隐私论文?
ICML 2026 有 42 篇差分隐私论文,上一届是 47 篇。
CVPR 2026 有多少篇差分隐私论文?
CVPR 2026 有 7 篇差分隐私论文,上一届是 4 篇。
哪个会议的差分隐私论文最多?
NeurIPS,2023–2026 年共 217 篇。

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