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
- 理论 · learning theory论文从 2023 年的 86 篇增长到 2026 年的 482 篇,三年间扩大到约 5.6 倍。
- NeurIPS 是发理论 · learning theory论文最多的会议,2023–2026 年共 540 篇,占四个会议总量的 40%。
- 交叉方向里涨得最快的是社会层面 · accountability transparency and interpretability:同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 33 篇。
- 在「理论与统计」的 5 个主题里,它的 2026 年论文数排第 2;同组增长最快的理论 · optimization是 4.7 倍,理论 · learning theory是 5.6 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 57 | 24 | 5 | 0 | 86 |
| 2024 | 265 | 106 | 21 | 1 | 393 |
| 2025 | 106 | 147 | 132 | 4 | 389 |
| 2026 | 112 | 200 | 170 | 0 | 482 |
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
- NeurIPS 2026A dynamical systems theory of reward-modulated learning in linear recurrent networks
- ICML 2026A Fine-Grained Understanding of Uniform Convergence for Halfspaces
- ICLR 2026A Law of Data Reconstruction for Random Features (And Beyond)
- NeurIPS 2025A Geometric Analysis of PCA
- ICML 2025A Generalization Theory for Zero-Shot Prediction
- ICLR 2025A Solvable Attention for Neural Scaling Laws
- CVPR 2025Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation
- NeurIPS 20244+3 Phases of Compute-Optimal Neural Scaling Laws
- ICML 2024A Statistical Theory of Regularization-Based Continual Learning
- ICLR 2024A Sublinear Adversarial Training Algorithm
- CVPR 2024Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory
- NeurIPS 2023$\varepsilon$-fractional core stability in Hedonic Games.
- ICML 2023Robust Collaborative Learning with Linear Gradient Overhead
- ICLR 2023Bispectral Neural Networks
- NeurIPS 2026A Mechanistic Investigation of Theory of Mind in a Large Language Model
- ICML 2026A Random Matrix Theory of Masked Self-Supervised Learning
- ICLR 2026A New Approach to Controlling Linear Dynamical Systems
- NeurIPS 2025Approximation theory for 1-Lipschitz ResNets
- ICML 2025A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
- ICLR 2025A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
全部理论 · learning theory论文
共 540 篇,第 8 / 11 页
- NeurIPS 2024Linear Regression using Heterogeneous Data Batches
- NeurIPS 2024Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization
- NeurIPS 2024Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages
- NeurIPS 2024Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods
- NeurIPS 2024Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input
- NeurIPS 2024Metric Transforms and Low Rank Representations of Kernels for Fast Attention
- NeurIPS 2024Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
- NeurIPS 2024Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
- NeurIPS 2024Model Collapse Demystified: The Case of Regression
- NeurIPS 2024Multi-Label Learning with Stronger Consistency Guarantees
- NeurIPS 2024Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
- NeurIPS 2024Nature-Inspired Local Propagation
- NeurIPS 2024Near-Optimality of Contrastive Divergence Algorithms
- NeurIPS 2024Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms
- NeurIPS 2024Neural Collapse To Multiple Centers For Imbalanced Data
- NeurIPS 2024Neural Conditional Probability for Uncertainty Quantification
- NeurIPS 2024Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit
- NeurIPS 2024NeuralClothSim: Neural Deformation Fields Meet the Thin Shell Theory
- NeurIPS 2024Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom
- NeurIPS 2024Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
- NeurIPS 2024Non-asymptotic Convergence of Training Transformers for Next-token Prediction
- NeurIPS 2024Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks
- NeurIPS 2024Occupancy-based Policy Gradient: Estimation, Convergence, and Optimality
- NeurIPS 2024On $f$-Divergence Principled Domain Adaptation: An Improved Framework
- NeurIPS 2024On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
- NeurIPS 2024On the Ability of Developers' Training Data Preservation of Learnware
- NeurIPS 2024On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
- NeurIPS 2024On the Computational Landscape of Replicable Learning
- NeurIPS 2024On the Curses of Future and History in Future-dependent Value Functions for Off-policy Evaluation
- NeurIPS 2024On the Efficiency of ERM in Feature Learning
- NeurIPS 2024On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
- NeurIPS 2024On the Limitations of Fractal Dimension as a Measure of Generalization
- NeurIPS 2024On the Power of Decision Trees in Auto-Regressive Language Modeling
- NeurIPS 2024On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
- NeurIPS 2024On the Role of Attention Masks and LayerNorm in Transformers
- NeurIPS 2024On the Saturation Effects of Spectral Algorithms in Large Dimensions
- NeurIPS 2024On the Sparsity of the Strong Lottery Ticket Hypothesis
- NeurIPS 2024On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity
- NeurIPS 2024One-Layer Transformer Provably Learns One-Nearest Neighbor In Context
- NeurIPS 2024Online Consistency of the Nearest Neighbor Rule
- NeurIPS 2024Online Weighted Paging with Unknown Weights
- NeurIPS 2024Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
- NeurIPS 2024Optimal Algorithms for Augmented Testing of Discrete Distributions
- NeurIPS 2024Optimal Algorithms for Learning Partitions with Faulty Oracles
- NeurIPS 2024Optimal deep learning of holomorphic operators between Banach spaces
- NeurIPS 2024Optimal Hypothesis Selection in (Almost) Linear Time
- NeurIPS 2024Optimal Parallelization of Boosting
- NeurIPS 2024Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime
- NeurIPS 2024Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms
- NeurIPS 2024Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
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用 paperlist 查理论 · learning theory在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
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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。