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 958 篇，第 16 / 20 页

  1. NeurIPS 2024Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
  2. NeurIPS 2024Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
  3. NeurIPS 2024Sketching for Distributed Deep Learning: A Sharper Analysis
  4. NeurIPS 2024SkipPredict: When to Invest in Predictions for Scheduling
  5. NeurIPS 2024SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
  6. NeurIPS 2024SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
  7. NeurIPS 2024Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation
  8. NeurIPS 2024Stabilized Proximal-Point Methods for Federated Optimization
  9. NeurIPS 2024Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
  10. NeurIPS 2024Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
  11. NeurIPS 2024Stochastic Newton Proximal Extragradient Method
  12. NeurIPS 2024Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data
  13. NeurIPS 2024Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
  14. NeurIPS 2024Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
  15. NeurIPS 2024Stopping Bayesian Optimization with Probabilistic Regret Bounds
  16. NeurIPS 2024Super Consistency of Neural Network Landscapes and Learning Rate Transfer
  17. NeurIPS 2024SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
  18. NeurIPS 2024Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
  19. NeurIPS 2024The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
  20. NeurIPS 2024The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
  21. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
  22. NeurIPS 2024The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
  23. NeurIPS 2024The Implicit Bias of Adam on Separable Data
  24. NeurIPS 2024The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
  25. NeurIPS 2024The Power of Extrapolation in Federated Learning
  26. NeurIPS 2024The Road Less Scheduled
  27. NeurIPS 2024The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
  28. NeurIPS 2024The Space Complexity of Approximating Logistic Loss
  29. NeurIPS 2024The Star Geometry of Critic-Based Regularizer Learning
  30. NeurIPS 2024Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks
  31. NeurIPS 2024There is No Silver Bullet: Benchmarking Methods in Predictive Combinatorial Optimization
  32. NeurIPS 2024This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
  33. NeurIPS 2024Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
  34. NeurIPS 2024Topological obstruction to the training of shallow ReLU neural networks
  35. NeurIPS 2024Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models
  36. NeurIPS 2024Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression
  37. NeurIPS 2024Transition Constrained Bayesian Optimization via Markov Decision Processes
  38. NeurIPS 2024TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
  39. NeurIPS 2024UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
  40. NeurIPS 2024Universal Neural Functionals
  41. NeurIPS 2024Universal Online Convex Optimization with $1$ Projection per Round
  42. NeurIPS 2024Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
  43. NeurIPS 2024Unraveling the Gradient Descent Dynamics of Transformers
  44. NeurIPS 2024Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization
  45. NeurIPS 2024UQ-Guided Hyperparameter Optimization for Iterative Learners
  46. NeurIPS 2024UQE: A Query Engine for Unstructured Databases
  47. NeurIPS 2024Variational Delayed Policy Optimization
  48. NeurIPS 2024Warm-starting Push-Relabel
  49. NeurIPS 2024Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
  50. NeurIPS 2024Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness

在 Claude、Cursor 里直接问这个趋势

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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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