理论 · learning theory论文趋势 2023–2026

学习理论及相关：learning_theory

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,350 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

理论 · learning theory论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202357245086
2024265106211393
20251061471324389
20261122001700482

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

全部理论 · learning theory论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,350 篇，第 27 / 27 页

  1. NeurIPS 2023Bandit Social Learning under Myopic Behavior
  2. NeurIPS 2023Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
  3. NeurIPS 2023Bridging RL Theory and Practice with the Effective Horizon
  4. NeurIPS 2023Characterization of Overfitting in Robust Multiclass Classification
  5. NeurIPS 2023Common Ground in Cooperative Communication
  6. NeurIPS 2023Delegated Classification
  7. NeurIPS 2023Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback
  8. NeurIPS 2023Equivariant Neural Operator Learning with Graphon Convolution
  9. NeurIPS 2023Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
  10. NeurIPS 2023Faster Relative Entropy Coding with Greedy Rejection Coding
  11. NeurIPS 2023Feature Selection in the Contrastive Analysis Setting
  12. NeurIPS 2023Finding Safe Zones of Markov Decision Processes Policies
  13. NeurIPS 2023Generalized Belief Transport
  14. NeurIPS 2023Information Theoretic Lower Bounds for Information Theoretic Upper Bounds
  15. NeurIPS 2023Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective
  16. NeurIPS 2023Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
  17. NeurIPS 2023Max-Sliced Mutual Information
  18. NeurIPS 2023Nash Regret Guarantees for Linear Bandits
  19. NeurIPS 2023Near-Linear Time Algorithm for the Chamfer Distance
  20. NeurIPS 2023New Bounds for Hyperparameter Tuning of Regression Problems Across Instances
  21. NeurIPS 2023No-regret Algorithms for Fair Resource Allocation
  22. NeurIPS 2023On Generalization Bounds for Projective Clustering
  23. NeurIPS 2023On kernel-based statistical learning theory in the mean field limit
  24. NeurIPS 2023On Slicing Optimality for Mutual Information
  25. NeurIPS 2023On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm
  26. NeurIPS 2023Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games
  27. NeurIPS 2023Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation
  28. NeurIPS 2023Provable benefits of score matching
  29. NeurIPS 2023Provably Safe Reinforcement Learning with Step-wise Violation Constraints
  30. NeurIPS 2023Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
  31. NeurIPS 2023Reliable learning in challenging environments
  32. NeurIPS 2023Replicability in Reinforcement Learning
  33. NeurIPS 2023Replicable Clustering
  34. NeurIPS 2023Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
  35. NeurIPS 2023Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms
  36. NeurIPS 2023Sharp Spectral Rates for Koopman Operator Learning
  37. NeurIPS 2023Similarity-based cooperative equilibrium
  38. NeurIPS 2023Smoothed Analysis of Sequential Probability Assignment
  39. NeurIPS 2023Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory
  40. NeurIPS 2023Strategic Data Sharing between Competitors
  41. NeurIPS 2023Structured Prediction with Stronger Consistency Guarantees
  42. NeurIPS 2023Temporally Disentangled Representation Learning under Unknown Nonstationarity
  43. NeurIPS 2023The Crucial Role of Normalization in Sharpness-Aware Minimization
  44. NeurIPS 2023The noise level in linear regression with dependent data
  45. NeurIPS 2023Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
  46. NeurIPS 2023Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection
  47. NeurIPS 2023Two-Stage Learning to Defer with Multiple Experts
  48. NeurIPS 2023What can a Single Attention Layer Learn? A Study Through the Random Features Lens
  49. NeurIPS 2023When are ensembles really effective?
  50. NeurIPS 2023Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria

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 查理论 · learning theory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": "theory-learning-theory"}

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理论 · learning theory论文？
共 1,350 篇，按年份分别是 2023 年 86 篇、2024 年 393 篇、2025 年 389 篇、2026 年 482 篇。
NeurIPS 2026 有多少篇理论 · learning theory论文？
NeurIPS 2026 有 112 篇理论 · learning theory论文，上一届是 106 篇。
ICLR 2026 有多少篇理论 · learning theory论文？
ICLR 2026 有 200 篇理论 · learning theory论文，上一届是 147 篇。
ICML 2026 有多少篇理论 · learning theory论文？
ICML 2026 有 170 篇理论 · learning theory论文，上一届是 132 篇。
CVPR 2025 有多少篇理论 · learning theory论文？
CVPR 2025 有 4 篇理论 · learning theory论文，上一届是 1 篇。
哪个会议的理论 · learning theory论文最多？
NeurIPS，2023–2026 年共 540 篇。

「理论与统计」下的其他主题