深度学习 · optimization论文趋势 2023–2026

主要结论

• 深度学习 · optimization论文从 2023 年的 256 篇降到 2026 年的 240 篇，热度在回落。
• NeurIPS 是发深度学习 · optimization论文最多的会议，2023–2026 年共 500 篇，占四个会议总量的 52%。
• 交叉方向里涨得最快的是对齐与安全：同时属于两个主题的论文从 2023 年的 5 篇增至 2026 年的 23 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 6；同组增长最快的扩散模型是 4.1 倍，深度学习 · optimization是 0.9 倍。

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

• NeurIPS 2026Achieving Directional-Stationarity from a Single Random Direction Step
• ICML 2026Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
• ICLR 2026From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
• CVPR 2026Coverage Optimization for Camera View Selection
• NeurIPS 2025High-Performance Arithmetic Circuit Optimization via Differentiable Architecture Search
• ICML 2025Feature-Mapping Topology Optimization with Neural Heaviside Signed Distance Functions
• ICLR 2025Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
• CVPR 2025HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition
• NeurIPS 2024$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
• ICML 2024Barrier Algorithms for Constrained Non-Convex Optimization
• ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
• CVPR 2024Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
• NeurIPS 2023$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning
• ICML 2023Buying Information for Stochastic Optimization
• ICLR 2023Alternating Differentiation for Optimization Layers
• CVPR 2023Visual-Language Prompt Tuning With Knowledge-Guided Context Optimization
• NeurIPS 2026Adaptive Conditional Gradient Sliding: Projection-Free and Line-Search-Free Acceleration
• ICML 2026Riemannian Optimization for Fair Spectral Clustering
• ICLR 2026Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective
• CVPR 2026Its Never Too Late Noise Optimization for Collapse Recovery in

全部深度学习 · optimization论文

共 144 篇，第 1 / 3 页

1. NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
2. NeurIPS 2023$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning
3. NeurIPS 2023A Computationally Efficient Sparsified Online Newton Method
4. NeurIPS 2023A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability
5. NeurIPS 2023A Guide Through the Zoo of Biased SGD
6. NeurIPS 2023A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization
7. NeurIPS 2023A Unified Approach for Maximizing Continuous DR-submodular Functions
8. NeurIPS 2023A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
9. NeurIPS 2023Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization
10. NeurIPS 2023Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
11. NeurIPS 2023Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
12. NeurIPS 2023Adjustable Robust Reinforcement Learning for Online 3D Bin Packing
13. NeurIPS 2023Advancing Bayesian Optimization via Learning Correlated Latent Space
14. NeurIPS 2023Algorithmic Regularization in Tensor Optimization: Towards a Lifted Approach in Matrix Sensing
15. NeurIPS 2023An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
16. NeurIPS 2023An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits
17. NeurIPS 2023An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
18. NeurIPS 2023Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger
19. NeurIPS 2023Bayesian Optimization with Cost-varying Variable Subsets
20. NeurIPS 2023Behavior Alignment via Reward Function Optimization
21. NeurIPS 2023Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
22. NeurIPS 2023Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time
23. NeurIPS 2023Bi-Level Offline Policy Optimization with Limited Exploration
24. NeurIPS 2023Bicriteria Approximation Algorithms for the Submodular Cover Problem
25. NeurIPS 2023Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start
26. NeurIPS 2023Birder: Communication-Efficient 1-bit Adaptive Optimizer for Practical Distributed DNN Training
27. NeurIPS 2023BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization
28. NeurIPS 2023Block Low-Rank Preconditioner with Shared Basis for Stochastic Optimization
29. NeurIPS 2023Boosting with Tempered Exponential Measures
30. NeurIPS 2023BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial Optimization
31. NeurIPS 2023Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits
32. NeurIPS 2023Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems
33. NeurIPS 2023Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
34. NeurIPS 2023Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning
35. NeurIPS 2023Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning
36. NeurIPS 2023Contextual Stochastic Bilevel Optimization
37. NeurIPS 2023Convergence of Adam Under Relaxed Assumptions
38. NeurIPS 2023CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
39. NeurIPS 2023Data-driven Optimal Filtering for Linear Systems with Unknown Noise Covariances
40. NeurIPS 2023Debiasing Conditional Stochastic Optimization
41. NeurIPS 2023DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
42. NeurIPS 2023Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization
43. NeurIPS 2023Distributionally Robust Bayesian Optimization with $\varphi$-divergences
44. NeurIPS 2023Distributionally Robust Linear Quadratic Control
45. NeurIPS 2023Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models
46. NeurIPS 2023DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
47. NeurIPS 2023DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization
48. NeurIPS 2023DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework
49. NeurIPS 2023Efficient Activation Function Optimization through Surrogate Modeling
50. NeurIPS 2023Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization

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。