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 44 / 47 页

  1. ICML 2023Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization
  2. ICML 2023Optimal Shrinkage for Distributed Second-Order Optimization
  3. ICML 2023Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
  4. ICML 2023Optimization for Amortized Inverse Problems
  5. ICML 2023PASTA: Pessimistic Assortment Optimization
  6. ICML 2023Quantized Distributed Training of Large Models with Convergence Guarantees
  7. ICML 2023Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
  8. ICML 2023Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds
  9. ICML 2023Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization
  10. ICML 2023Revisiting Sampling for Combinatorial Optimization
  11. ICML 2023Second-Order Optimization with Lazy Hessians
  12. ICML 2023Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction
  13. ICML 2023Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.
  14. ICML 2023Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function
  15. ICML 2023SLAMB: Accelerated Large Batch Training with Sparse Communication
  16. ICML 2023Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels
  17. ICML 2023Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks
  18. ICML 2023Submodular Order Functions and Assortment Optimization
  19. ICML 2023SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems
  20. ICML 2023Target-based Surrogates for Stochastic Optimization
  21. ICML 2023Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
  22. ICML 2023Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes
  23. ICML 2023Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization
  24. ICML 2023Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy
  25. ICML 2023Understand and Modularize Generator Optimization in ELECTRA-style Pretraining
  26. ICML 2023User-level Private Stochastic Convex Optimization with Optimal Rates
  27. NeurIPS 2023(Amplified) Banded Matrix Factorization: A unified approach to private training
  28. NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
  29. NeurIPS 20232Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression
  30. NeurIPS 2023A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
  31. NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
  32. NeurIPS 2023A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
  33. NeurIPS 2023A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization
  34. NeurIPS 2023A Unified Approach for Maximizing Continuous DR-submodular Functions
  35. NeurIPS 2023A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
  36. NeurIPS 2023A Unified Framework for Rank-based Loss Minimization
  37. NeurIPS 2023Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization
  38. NeurIPS 2023Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
  39. NeurIPS 2023Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
  40. NeurIPS 2023Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction
  41. NeurIPS 2023Advancing Bayesian Optimization via Learning Correlated Latent Space
  42. NeurIPS 2023An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
  43. NeurIPS 2023An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits
  44. NeurIPS 2023An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
  45. NeurIPS 2023An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions
  46. NeurIPS 2023AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
  47. NeurIPS 2023Batch Bayesian Optimization For Replicable Experimental Design
  48. NeurIPS 2023Bias in Evaluation Processes: An Optimization-Based Model
  49. NeurIPS 2023Bicriteria Approximation Algorithms for the Submodular Cover Problem
  50. NeurIPS 2023Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start

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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