理论 · optimization论文趋势 2023–2026
学习理论及相关：optimization
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,871 篇被归入该主题的论文。
主要结论
- 理论 · optimization论文从 2023 年的 123 篇增长到 2026 年的 584 篇，三年间扩大到约 4.7 倍。
- NeurIPS 是发理论 · optimization论文最多的会议，2023–2026 年共 778 篇，占四个会议总量的 42%。
- 交叉方向里涨得最快的是低秩适配：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 31 篇。
- 在「理论与统计」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的理论 · learning theory是 5.6 倍，理论 · optimization是 4.7 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 37 | 46 | 35 | 5 | 123 |
| 2024 | 304 | 123 | 67 | 0 | 494 |
| 2025 | 318 | 196 | 147 | 9 | 670 |
| 2026 | 119 | 244 | 214 | 7 | 584 |
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 2026A Mechanistic Investigation of Theory of Mind in a Large Language Model
- ICML 2026A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
- ICLR 2026A Convergence Analysis of Adaptive Optimizers under Floating-point Quantization
- CVPR 2026TriSim Tri-Dimensional Similarity Modeling with Extreme Value Theory for False-Negative
- NeurIPS 20253BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs
- ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
- ICLR 2025A Coefficient Makes SVRG Effective
- CVPR 2025Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation
- NeurIPS 2024A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
- ICML 2024A Statistical Theory of Regularization-Based Continual Learning
- ICLR 2024A Discretization Framework for Robust Contextual Stochastic Optimization
- NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
- ICML 2023Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
- ICLR 2023Adaptive Optimization in the $\infty$-Width Limit
- CVPR 2023Deep Hashing With Minimal-Distance-Separated Hash Centers
- NeurIPS 2026Avoiding Obfuscation with Prover-Estimator Debate
- ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
- ICLR 2026A Memory-Efficient Hierarchical Algorithm for Large-scale Optimal Transport Problems
- CVPR 2026FedAdamom Adaptive Momentum for Improved Generalization in Federated Optimization
- NeurIPS 2025A Beyond-Worst-Case Analysis of Greedy k-means++
全部理论 · optimization论文
共 244 篇，第 5 / 5 页
- ICLR 2026Sign-SGD via Parameter-Free Optimization
- ICLR 2026Single-Loop Byzantine-Resilient Federated Bilevel Optimization
- ICLR 2026Sobolev Gradient Ascent for Optimal Transport: Barycenter Optimization and Convergence Analysis
- ICLR 2026Soft Quality-Diversity Optimization
- ICLR 2026Solving the 2-norm k-hyperplane clustering problem via multi-norm formulations
- ICLR 2026Special Unitary Parameterized Estimators of Rotation
- ICLR 2026Statistical Advantage of Softmax Attention: Insights from Single-Location Regression
- ICLR 2026StepORLM: A Self-Evolving Framework With Generative Process Supervision For Operations Research Language Models
- ICLR 2026Stop Guessing: Choosing the Optimization-Consistent Uncertainty Measurement for Evidential Deep Learning
- ICLR 2026Strong Correlations Induce Cause Only Predictions in Transformer Training
- ICLR 2026Strongly Convex Sets in Riemannian Manifolds
- ICLR 2026Sublinear Time Quantum Algorithm for Attention Approximation
- ICLR 2026Submodular Function Minimization with Dueling Oracle
- ICLR 2026SupCLAP: Controlling Optimization Trajectory Drift in Audio-Text Contrastive Learning with Support Vector Regularization
- ICLR 2026SVD Provably Denoises Nearest Neighbor Data
- ICLR 2026T-TAMER: Provably Taming Trade-offs in ML Serving
- ICLR 2026Task-free Adaptive Meta Black-box Optimization
- ICLR 2026The Effect of Attention Head Count on Transformer Approximation
- ICLR 2026The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm
- ICLR 2026The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton
- ICLR 2026The Power of Small Initialization in Noisy Low-Tubal-Rank Tensor Recovery
- ICLR 2026Thompson Sampling via Fine-Tuning of LLMs
- ICLR 2026Three Forward, One Backward: Memory-Efficient Full-Rank Fine-Tuning of Large Models via Extra Forward Passes
- ICLR 2026Tighter Performance Theory of FedExProx
- ICLR 2026Towards a Sharp Analysis of Learning Offline $f$-Divergence-Regularized Contextual Bandits
- ICLR 2026Towards Dynamic Interleaving Optimizers
- ICLR 2026Towards Efficient Constraint Handling in Neural Solvers for Routing Problems
- ICLR 2026Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension
- ICLR 2026Towards Safe and Optimal Online Bidding: A Modular Look-ahead Lyapunov Framework
- ICLR 2026Towards Understanding The Calibration Benefits of Sharpness-Aware Minimization
- ICLR 2026Tractability via Low Dimensionality: The Parameterized Complexity of Training Quantized Neural Networks
- ICLR 2026Training Dynamics Impact Post-Training Quantization Robustness
- ICLR 2026Tuning the burn-in phase in training recurrent neural networks improves their performance
- ICLR 2026TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
- ICLR 2026Two (narrow) heads are better than (an arbitrarily wide) one
- ICLR 2026Two-Layer Convolutional Autoencoders Trained on Normal Data Provably Detect Unseen Anomalies
- ICLR 2026Unbiased Gradient Estimation for Event Binning via Functional Backpropagation
- ICLR 2026Understanding and improving Shampoo and SOAP via Kullback-Leibler Minimization
- ICLR 2026Unified Analyses for Hierarchical Federated Learning: Topology Selection under Data Heterogeneity
- ICLR 2026Unlocking the Potential of Weighting Methods in Federated Learning Through Communication Compression
- ICLR 2026Vision-Zero: Scalable VLM Self-Improvement via Strategic Gamified Self-Play
- ICLR 2026ViTSP: A Vision Language Models Guided Framework for Large-Scale Traveling Salesman Problems
- ICLR 2026Why Less is More (Sometimes): A Theory of Data Curation
- ICLR 2026WILD-Diffusion: A WDRO Inspired Training Method for Diffusion Models under Limited Data
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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。
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用 paperlist 查理论 · 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": "theory-optimization"}
常见问题
- 2023–2026 年四大会议一共有多少篇理论 · optimization论文？
- 共 1,871 篇，按年份分别是 2023 年 123 篇、2024 年 494 篇、2025 年 670 篇、2026 年 584 篇。
- NeurIPS 2026 有多少篇理论 · optimization论文？
- NeurIPS 2026 有 119 篇理论 · optimization论文，上一届是 318 篇。
- ICLR 2026 有多少篇理论 · optimization论文？
- ICLR 2026 有 244 篇理论 · optimization论文，上一届是 196 篇。
- ICML 2026 有多少篇理论 · optimization论文？
- ICML 2026 有 214 篇理论 · optimization论文，上一届是 147 篇。
- CVPR 2026 有多少篇理论 · optimization论文？
- CVPR 2026 有 7 篇理论 · optimization论文，上一届是 9 篇。
- 哪个会议的理论 · optimization论文最多？
- NeurIPS，2023–2026 年共 778 篇。