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 5 / 27 页

  1. ICML 2026A Decision-Theoretic View of Test-Time Training: When, How Far, and Which Directions to Adapt
  2. ICML 2026A Fine-Grained Understanding of Uniform Convergence for Halfspaces
  3. ICML 2026A General Framework for Fair and Robust Regression
  4. ICML 2026A Random Matrix Perspective on the Consistency of Diffusion Models
  5. ICML 2026A Random Matrix Theory of Masked Self-Supervised Learning
  6. ICML 2026A Refined Generalization Analysis for Extreme Multi-class Supervised Contrastive Representation Learning
  7. ICML 2026A Risk Decomposition Framework for Pre-hoc Fine-tuning Prediction
  8. ICML 2026A Solvable High-Dimensional Model Where Nonlinear Autoencoders Learn Structure Invisible to PCA While Test Loss Misaligns With Generalization
  9. ICML 2026A Task-centric Theory for Iterative Self-Improvement with Easy-to-Hard Curricula
  10. ICML 2026A Theoretical Framework for Statistical Evaluability of Generative Models
  11. ICML 2026A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning
  12. ICML 2026A theory of learning data statistics in diffusion models, from easy to hard
  13. ICML 2026Active Learning with Low-Rank Structure for Data Selection
  14. ICML 2026Adaptive Preconditioners Trigger Loss Spikes in Adam
  15. ICML 2026Adversarially Robust Approximate Furthest Neighbor
  16. ICML 2026AI4SLT: Empirical Processes in Lean 4 for Formal Statistical Learning Theory
  17. ICML 2026Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
  18. ICML 2026All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension
  19. ICML 2026An Algebraic View of the Expressivity of Recurrent Language Models
  20. ICML 2026An analytic theory of convolutional neural network inverse problems solvers
  21. ICML 2026An Efficient Joint Learning Approach for Item Response Theory
  22. ICML 2026Approximate Equivariance via Projection-Based Regularisation
  23. ICML 2026Approximation Error Upper and Lower Bounds for Hölder Class with Transformers
  24. ICML 2026Approximation Theory for Lipschitz Continuous Transformers
  25. ICML 2026Asymptotic Theory of Iterated Empirical Risk Minimization, with Applications to Active Learning
  26. ICML 2026Asymptotically Fast Clebsch-Gordan Tensor Products with Vector Spherical Harmonics
  27. ICML 2026Benign Overfitting in Adversarial Training for Vision Transformers
  28. ICML 2026Beyond Binary: Continuous State Optimization with Graph-Structured Objectives
  29. ICML 2026Black-Box Assisted Regression: Phase Transitions and Minimax Optimality
  30. ICML 2026Breaking the Reversal Curse in Autoregressive Language Models via Identity Bridge
  31. ICML 2026Certifying Capabilities from Finite Tests: When Is It Possible?
  32. ICML 2026Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
  33. ICML 2026Characterizing the Effect of Noise in Language Generation in the Limit
  34. ICML 2026Combinatorial Sparse PCA Beyond the Spiked Identity Model
  35. ICML 2026Consistency Deep Equilibrium Models
  36. ICML 2026Continuous Variable Hamiltonian Learning at Heisenberg Limit via Displacement-Random Unitary Transformation
  37. ICML 2026Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation
  38. ICML 2026Correcting Overparameterization Effects in Fair Empirical Risk Minimization
  39. ICML 2026Coupled Training with Privileged Information and Unlabeled Data
  40. ICML 2026Coverage Improvement and Fast Convergence of On-policy Preference Learning
  41. ICML 2026Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks
  42. ICML 2026Decision Tree Learning on Product Spaces
  43. ICML 2026Decomposing Out-of-Distribution Error in Conditional Flow Matching via Wasserstein Geometry
  44. ICML 2026Deep Learning of Compositional Targets with Hierarchical Spectral Methods
  45. ICML 2026Deep Networks Learn Deep Hierarchical Models
  46. ICML 2026Deep Neural Network Regression with Functional Covariates
  47. ICML 2026Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
  48. ICML 2026Diffusion Models Are Statistically Optimal for Learning Low-Dimensional Multi-Modal Distributions
  49. ICML 2026DPO Unchained: Your Training Algorithm is Secretly Disentangled in Human Choice Theory (and Its Loss' Convexity is Dispensable)
  50. ICML 2026Effective Model Pruning : Measuring the Redundancy of Model Components

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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。

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