深度学习 · optimization论文趋势 2023–2026

ICML/NeurIPS 深度学习方向：optimization

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 953 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

深度学习 · optimization论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202314434708256
202419130721294
20256251446163
202610344867240

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

全部深度学习 · optimization论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 256 篇，第 5 / 6 页

  1. NeurIPS 2023Momentum Provably Improves Error Feedback!
  2. NeurIPS 2023Neural Fields with Hard Constraints of Arbitrary Differential Order
  3. NeurIPS 2023Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization
  4. NeurIPS 2023Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement
  5. NeurIPS 2023Non-Convex Bilevel Optimization with Time-Varying Objective Functions
  6. NeurIPS 2023Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization
  7. NeurIPS 2023Online Control for Meta-optimization
  8. NeurIPS 2023Online Convex Optimization with Unbounded Memory
  9. NeurIPS 2023Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization
  10. NeurIPS 2023Online Learning under Adversarial Nonlinear Constraints
  11. NeurIPS 2023Optimization of Inter-group criteria for clustering with minimum size constraints
  12. NeurIPS 2023Outlier-Robust Gromov-Wasserstein for Graph Data
  13. NeurIPS 2023Parallel Submodular Function Minimization
  14. NeurIPS 2023Parallel-mentoring for Offline Model-based Optimization
  15. NeurIPS 2023Path following algorithms for $\ell_2$-regularized $M$-estimation with approximation guarantee
  16. NeurIPS 2023Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
  17. NeurIPS 2023Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games
  18. NeurIPS 2023Percentile Criterion Optimization in Offline Reinforcement Learning
  19. NeurIPS 2023Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
  20. NeurIPS 2023Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
  21. NeurIPS 2023Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
  22. NeurIPS 2023Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
  23. NeurIPS 2023Predict-then-Calibrate: A New Perspective of Robust Contextual LP
  24. NeurIPS 2023PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
  25. NeurIPS 2023Projection-Free Online Convex Optimization via Efficient Newton Iterations
  26. NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
  27. NeurIPS 2023Quantum Bayesian Optimization
  28. NeurIPS 2023Quantum speedups for stochastic optimization
  29. NeurIPS 2023Reduced Policy Optimization for Continuous Control with Hard Constraints
  30. NeurIPS 2023Regret Minimization via Saddle Point Optimization
  31. NeurIPS 2023Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions
  32. NeurIPS 2023Resetting the Optimizer in Deep RL: An Empirical Study
  33. NeurIPS 2023ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
  34. NeurIPS 2023Revisiting Implicit Differentiation for Learning Problems in Optimal Control
  35. NeurIPS 2023Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
  36. NeurIPS 2023Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
  37. NeurIPS 2023Riemannian stochastic optimization methods avoid strict saddle points
  38. NeurIPS 2023Robust Learning for Smoothed Online Convex Optimization with Feedback Delay
  39. NeurIPS 2023Sampling weights of deep neural networks
  40. NeurIPS 2023Self-Correcting Bayesian Optimization through Bayesian Active Learning
  41. NeurIPS 2023SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
  42. NeurIPS 2023Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions
  43. NeurIPS 2023SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization
  44. NeurIPS 2023Solving a Class of Non-Convex Minimax Optimization in Federated Learning
  45. NeurIPS 2023SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data
  46. NeurIPS 2023State Regularized Policy Optimization on Data with Dynamics Shift
  47. NeurIPS 2023Stochastic Approximation Approaches to Group Distributionally Robust Optimization
  48. NeurIPS 2023TD Convergence: An Optimization Perspective
  49. NeurIPS 2023Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
  50. NeurIPS 2023Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints

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 查深度学习 · 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": "dl-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深度学习 · optimization论文？
共 953 篇，按年份分别是 2023 年 256 篇、2024 年 294 篇、2025 年 163 篇、2026 年 240 篇。
NeurIPS 2026 有多少篇深度学习 · optimization论文？
NeurIPS 2026 有 103 篇深度学习 · optimization论文，上一届是 62 篇。
ICLR 2026 有多少篇深度学习 · optimization论文？
ICLR 2026 有 44 篇深度学习 · optimization论文，上一届是 51 篇。
ICML 2026 有多少篇深度学习 · optimization论文？
ICML 2026 有 86 篇深度学习 · optimization论文，上一届是 44 篇。
CVPR 2026 有多少篇深度学习 · optimization论文？
CVPR 2026 有 7 篇深度学习 · optimization论文，上一届是 6 篇。
哪个会议的深度学习 · optimization论文最多？
NeurIPS，2023–2026 年共 500 篇。

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