联邦学习论文趋势 2023–2026

跨设备联邦

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 460 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

联邦学习论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202354293420137
202430234020113
20253118231991
202642193721119

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

全部联邦学习论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 54 篇，第 1 / 2 页

  1. NeurIPS 2023(Amplified) Banded Matrix Factorization: A unified approach to private training
  2. NeurIPS 2023A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning
  3. NeurIPS 2023A3FL: Adversarially Adaptive Backdoor Attacks to Federated Learning
  4. NeurIPS 2023Convergence Analysis of Sequential Federated Learning on Heterogeneous Data
  5. NeurIPS 2023Correlation Aware Sparsified Mean Estimation Using Random Projection
  6. NeurIPS 2023Cross-modal Active Complementary Learning with Self-refining Correspondence
  7. NeurIPS 2023DELTA: Diverse Client Sampling for Fasting Federated Learning
  8. NeurIPS 2023DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning
  9. NeurIPS 2023Dynamic Personalized Federated Learning with Adaptive Differential Privacy
  10. NeurIPS 2023EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
  11. NeurIPS 2023Fast Optimal Locally Private Mean Estimation via Random Projections
  12. NeurIPS 2023Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer
  13. NeurIPS 2023Federated Compositional Deep AUC Maximization
  14. NeurIPS 2023Federated Conditional Stochastic Optimization
  15. NeurIPS 2023Federated Learning via Meta-Variational Dropout
  16. NeurIPS 2023Federated Learning with Bilateral Curation for Partially Class-Disjoint Data
  17. NeurIPS 2023Federated Learning with Manifold Regularization and Normalized Update Reaggregation
  18. NeurIPS 2023Federated Linear Bandits with Finite Adversarial Actions
  19. NeurIPS 2023Federated Multi-Objective Learning
  20. NeurIPS 2023Federated Spectral Clustering via Secure Similarity Reconstruction
  21. NeurIPS 2023FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
  22. NeurIPS 2023FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks
  23. NeurIPS 2023FedL2P: Federated Learning to Personalize
  24. NeurIPS 2023Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization
  25. NeurIPS 2023Flow: Per-instance Personalized Federated Learning
  26. NeurIPS 2023FLuID: Mitigating Stragglers in Federated Learning using Invariant Dropout
  27. NeurIPS 2023Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data
  28. NeurIPS 2023IBA: Towards Irreversible Backdoor Attacks in Federated Learning
  29. NeurIPS 2023Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates
  30. NeurIPS 2023Incentivized Communication for Federated Bandits
  31. NeurIPS 2023Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning
  32. NeurIPS 2023Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization
  33. NeurIPS 2023Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training
  34. NeurIPS 2023Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM
  35. NeurIPS 2023Momentum Provably Improves Error Feedback!
  36. NeurIPS 2023Multiply Robust Federated Estimation of Targeted Average Treatment Effects
  37. NeurIPS 2023One-Pass Distribution Sketch for Measuring Data Heterogeneity in Federated Learning
  38. NeurIPS 2023Optimal cross-learning for contextual bandits with unknown context distributions
  39. NeurIPS 2023PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning.
  40. NeurIPS 2023Private Federated Frequency Estimation: Adapting to the Hardness of the Instance
  41. NeurIPS 2023Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval
  42. NeurIPS 2023PTADisc: A Cross-Course Dataset Supporting Personalized Learning in Cold-Start Scenarios
  43. NeurIPS 2023RECESS Vaccine for Federated Learning: Proactive Defense Against Model Poisoning Attacks
  44. NeurIPS 2023Resilient Constrained Learning
  45. NeurIPS 2023SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
  46. NeurIPS 2023Solving a Class of Non-Convex Minimax Optimization in Federated Learning
  47. NeurIPS 2023SPACE: Single-round Participant Amalgamation for Contribution Evaluation in Federated Learning
  48. NeurIPS 2023Spectral Co-Distillation for Personalized Federated Learning
  49. NeurIPS 2023StableFDG: Style and Attention Based Learning for Federated Domain Generalization
  50. NeurIPS 2023Structured Federated Learning through Clustered Additive Modeling

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 查联邦学习在 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": "federated-learning"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

常见问题

2023–2026 年四大会议一共有多少篇联邦学习论文？
共 460 篇，按年份分别是 2023 年 137 篇、2024 年 113 篇、2025 年 91 篇、2026 年 119 篇。
NeurIPS 2026 有多少篇联邦学习论文？
NeurIPS 2026 有 42 篇联邦学习论文，上一届是 31 篇。
ICLR 2026 有多少篇联邦学习论文？
ICLR 2026 有 19 篇联邦学习论文，上一届是 18 篇。
ICML 2026 有多少篇联邦学习论文？
ICML 2026 有 37 篇联邦学习论文，上一届是 23 篇。
CVPR 2026 有多少篇联邦学习论文？
CVPR 2026 有 21 篇联邦学习论文，上一届是 19 篇。
哪个会议的联邦学习论文最多？
NeurIPS，2023–2026 年共 157 篇。

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