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 540 篇，第 9 / 11 页

  1. NeurIPS 2024PAC-Bayes-Chernoff bounds for unbounded losses
  2. NeurIPS 2024Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
  3. NeurIPS 2024Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context
  4. NeurIPS 2024Prospective Learning: Learning for a Dynamic Future
  5. NeurIPS 2024Provable Benefit of Cutout and CutMix for Feature Learning
  6. NeurIPS 2024Provable Benefits of Complex Parameterizations for Structured State Space Models
  7. NeurIPS 2024Provable Tempered Overfitting of Minimal Nets and Typical Nets
  8. NeurIPS 2024Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
  9. NeurIPS 2024Quantifying the Gain in Weak-to-Strong Generalization
  10. NeurIPS 2024Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
  11. NeurIPS 2024Randomized Truthful Auctions with Learning Agents
  12. NeurIPS 2024Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
  13. NeurIPS 2024Reciprocal Learning
  14. NeurIPS 2024Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss
  15. NeurIPS 2024Reliable Learning of Halfspaces under Gaussian Marginals
  16. NeurIPS 2024Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma
  17. NeurIPS 2024Replicable Uniformity Testing
  18. NeurIPS 2024Rethinking 3D Convolution in $\ell_p$-norm Space
  19. NeurIPS 2024Robust Mixture Learning when Outliers Overwhelm Small Groups
  20. NeurIPS 2024Robust Sparse Regression with Non-Isotropic Designs
  21. NeurIPS 2024Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
  22. NeurIPS 2024Sample-Efficient Agnostic Boosting
  23. NeurIPS 2024Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models
  24. NeurIPS 2024Scaling laws for learning with real and surrogate data
  25. NeurIPS 2024Scaling Laws in Linear Regression: Compute, Parameters, and Data
  26. NeurIPS 2024Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
  27. NeurIPS 2024Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
  28. NeurIPS 2024Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics
  29. NeurIPS 2024Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts
  30. NeurIPS 2024Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
  31. NeurIPS 2024Soft ascent-descent as a stable and flexible alternative to flooding
  32. NeurIPS 2024Solving Sparse \& High-Dimensional-Output Regression via Compression
  33. NeurIPS 2024Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness
  34. NeurIPS 2024Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
  35. NeurIPS 2024Statistical Multicriteria Benchmarking via the GSD-Front
  36. NeurIPS 2024Statistical-Computational Trade-offs for Density Estimation
  37. NeurIPS 2024Stratified Prediction-Powered Inference for Effective Hybrid Evaluation of Language Models
  38. NeurIPS 2024Supervised Kernel Thinning
  39. NeurIPS 2024Surge Phenomenon in Optimal Learning Rate and Batch Size Scaling
  40. NeurIPS 2024Symmetric Linear Bandits with Hidden Symmetry
  41. NeurIPS 2024Testably Learning Polynomial Threshold Functions
  42. NeurIPS 2024The Benefits of Balance: From Information Projections to Variance Reduction
  43. NeurIPS 2024The Fine-Grained Complexity of Gradient Computation for Training Large Language Models
  44. NeurIPS 2024The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
  45. NeurIPS 2024The Implicit Bias of Gradient Descent on Separable Multiclass Data
  46. NeurIPS 2024The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions
  47. NeurIPS 2024The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing
  48. NeurIPS 2024The Many Faces of Optimal Weak-to-Strong Learning
  49. NeurIPS 2024The Minimax Rate of HSIC Estimation for Translation-Invariant Kernels
  50. NeurIPS 2024The Power of Hard Attention Transformers on Data Sequences: A formal language theoretic perspective

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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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