非凸优化论文趋势 2023–2026

收敛与 landscape

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 2,330 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

非凸优化论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023154799815346
202427510716018560
202527917719219667
202625017828643757

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

全部非凸优化论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 2,330 篇，第 37 / 47 页

  1. NeurIPS 2024Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem
  2. NeurIPS 2024Fundamental Convergence Analysis of Sharpness-Aware Minimization
  3. NeurIPS 2024Generalized Fast Exact Conformalization
  4. NeurIPS 2024Geodesic Optimization for Predictive Shift Adaptation on EEG data
  5. NeurIPS 2024Gliding over the Pareto Front with Uniform Designs
  6. NeurIPS 2024Global Convergence in Training Large-Scale Transformers
  7. NeurIPS 2024Globally Convergent Variational Inference
  8. NeurIPS 2024Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
  9. NeurIPS 2024Gradient Guidance for Diffusion Models: An Optimization Perspective
  10. NeurIPS 2024Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
  11. NeurIPS 2024Great Minds Think Alike: The Universal Convergence Trend of Input Salience
  12. NeurIPS 2024Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame
  13. NeurIPS 2024Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models
  14. NeurIPS 2024High-probability complexity bounds for stochastic non-convex minimax optimization
  15. NeurIPS 2024How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization?
  16. NeurIPS 2024How does Gradient Descent Learn Features --- A Local Analysis for Regularized Two-Layer Neural Networks
  17. NeurIPS 2024How does PDE order affect the convergence of PINNs?
  18. NeurIPS 2024Implicit Optimization Bias of Next-token Prediction in Linear Models
  19. NeurIPS 2024Implicit Regularization of Decentralized Gradient Descent for Sparse Regression
  20. NeurIPS 2024Improved Particle Approximation Error for Mean Field Neural Networks
  21. NeurIPS 2024Improved Regret for Bandit Convex Optimization with Delayed Feedback
  22. NeurIPS 2024Improving Deep Learning Optimization through Constrained Parameter Regularization
  23. NeurIPS 2024Improving Equivariant Model Training via Constraint Relaxation
  24. NeurIPS 2024Improving Generalization and Convergence by Enhancing Implicit Regularization
  25. NeurIPS 2024Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity
  26. NeurIPS 2024In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization
  27. NeurIPS 2024In-Context Learning State Vector with Inner and Momentum Optimization
  28. NeurIPS 2024Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery
  29. NeurIPS 2024Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence
  30. NeurIPS 2024Inversion-based Latent Bayesian Optimization
  31. NeurIPS 2024IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs
  32. NeurIPS 2024Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?
  33. NeurIPS 2024John Ellipsoids via Lazy Updates
  34. NeurIPS 2024Large Stepsize Gradient Descent for Non-Homogeneous Two-Layer Networks: Margin Improvement and Fast Optimization
  35. NeurIPS 2024Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities
  36. NeurIPS 2024Learnability of high-dimensional targets by two-parameter models and gradient flow
  37. NeurIPS 2024Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
  38. NeurIPS 2024Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
  39. NeurIPS 2024Learning Cut Generating Functions for Integer Programming
  40. NeurIPS 2024Learning Elastic Costs to Shape Monge Displacements
  41. NeurIPS 2024Learning from Noisy Labels via Conditional Distributionally Robust Optimization
  42. NeurIPS 2024Learning Generalized Linear Programming Value Functions
  43. NeurIPS 2024Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way
  44. NeurIPS 2024Learning with Fitzpatrick Losses
  45. NeurIPS 2024Learning-Augmented Dynamic Submodular Maximization
  46. NeurIPS 2024Length Optimization in Conformal Prediction
  47. NeurIPS 2024LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch
  48. NeurIPS 2024Linear Transformers are Versatile In-Context Learners
  49. NeurIPS 2024Localized Zeroth-Order Prompt Optimization
  50. NeurIPS 2024Loss Landscape Characterization of Neural Networks without Over-Parametrization

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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 查非凸优化在 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": "nonconvex-optimization"}

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常见问题

2023–2026 年四大会议一共有多少篇非凸优化论文？
共 2,330 篇，按年份分别是 2023 年 346 篇、2024 年 560 篇、2025 年 667 篇、2026 年 757 篇。
NeurIPS 2026 有多少篇非凸优化论文？
NeurIPS 2026 有 250 篇非凸优化论文，上一届是 279 篇。
ICLR 2026 有多少篇非凸优化论文？
ICLR 2026 有 178 篇非凸优化论文，上一届是 177 篇。
ICML 2026 有多少篇非凸优化论文？
ICML 2026 有 286 篇非凸优化论文，上一届是 192 篇。
CVPR 2026 有多少篇非凸优化论文？
CVPR 2026 有 43 篇非凸优化论文，上一届是 19 篇。
哪个会议的非凸优化论文最多？
NeurIPS，2023–2026 年共 958 篇。

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