理论 · optimization论文趋势 2023–2026

学习理论及相关：optimization

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,871 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 · optimization论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
20233746355123
2024304123670494
20253181961479670
20261192442147584

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 · optimization论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 778 篇，第 15 / 16 页

  1. NeurIPS 2024Symmetric Linear Bandits with Hidden Symmetry
  2. NeurIPS 2024Testably Learning Polynomial Threshold Functions
  3. NeurIPS 2024The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
  4. NeurIPS 2024The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
  5. NeurIPS 2024The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
  6. NeurIPS 2024The Implicit Bias of Gradient Descent on Separable Multiclass Data
  7. NeurIPS 2024The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing
  8. NeurIPS 2024The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
  9. NeurIPS 2024The Many Faces of Optimal Weak-to-Strong Learning
  10. NeurIPS 2024The Power of Extrapolation in Federated Learning
  11. NeurIPS 2024The Road Less Scheduled
  12. NeurIPS 2024The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
  13. NeurIPS 2024The Secretary Problem with Predicted Additive Gap
  14. NeurIPS 2024The Space Complexity of Approximating Logistic Loss
  15. NeurIPS 2024The Star Geometry of Critic-Based Regularizer Learning
  16. NeurIPS 2024There is No Silver Bullet: Benchmarking Methods in Predictive Combinatorial Optimization
  17. NeurIPS 2024Tight Bounds for Learning RUMs from Small Slates
  18. NeurIPS 2024Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
  19. NeurIPS 2024Tolerant Algorithms for Learning with Arbitrary Covariate Shift
  20. NeurIPS 2024Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms
  21. NeurIPS 2024Topological obstruction to the training of shallow ReLU neural networks
  22. NeurIPS 2024TorchOpt: An Efficient Library for Differentiable Optimization
  23. NeurIPS 2024Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models
  24. NeurIPS 2024Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning
  25. NeurIPS 2024Towards Exact Gradient-based Training on Analog In-memory Computing
  26. NeurIPS 2024Towards Scalable and Stable Parallelization of Nonlinear RNNs
  27. NeurIPS 2024Trade-Offs of Diagonal Fisher Information Matrix Estimators
  28. NeurIPS 2024Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis
  29. NeurIPS 2024Transductive Learning is Compact
  30. NeurIPS 2024Transition Constrained Bayesian Optimization via Markov Decision Processes
  31. NeurIPS 2024Universal Rates of Empirical Risk Minimization
  32. NeurIPS 2024Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
  33. NeurIPS 2024Unraveling the Gradient Descent Dynamics of Transformers
  34. NeurIPS 2024Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
  35. NeurIPS 2024UQ-Guided Hyperparameter Optimization for Iterative Learners
  36. NeurIPS 2024Variance estimation in compound decision theory under boundedness
  37. NeurIPS 2024Warm-starting Push-Relabel
  38. NeurIPS 2024Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
  39. NeurIPS 2024Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
  40. NeurIPS 2024Why Do We Need Weight Decay in Modern Deep Learning?
  41. NeurIPS 2024Why Transformers Need Adam: A Hessian Perspective
  42. NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
  43. NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
  44. NeurIPS 2023A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
  45. NeurIPS 2023Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization
  46. NeurIPS 2023Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
  47. NeurIPS 2023Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
  48. NeurIPS 2023Advancing Bayesian Optimization via Learning Correlated Latent Space
  49. NeurIPS 2023An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
  50. NeurIPS 2023Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start

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用 paperlist 查理论 · optimization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-optimization"}

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常见问题

2023–2026 年四大会议一共有多少篇理论 · optimization论文？
共 1,871 篇，按年份分别是 2023 年 123 篇、2024 年 494 篇、2025 年 670 篇、2026 年 584 篇。
NeurIPS 2026 有多少篇理论 · optimization论文？
NeurIPS 2026 有 119 篇理论 · optimization论文，上一届是 318 篇。
ICLR 2026 有多少篇理论 · optimization论文？
ICLR 2026 有 244 篇理论 · optimization论文，上一届是 196 篇。
ICML 2026 有多少篇理论 · optimization论文？
ICML 2026 有 214 篇理论 · optimization论文，上一届是 147 篇。
CVPR 2026 有多少篇理论 · optimization论文？
CVPR 2026 有 7 篇理论 · optimization论文，上一届是 9 篇。
哪个会议的理论 · optimization论文最多？
NeurIPS，2023–2026 年共 778 篇。

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