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 494 篇，第 4 / 10 页
- ICML 2024Improving SAM Requires Rethinking its Optimization Formulation
- ICML 2024KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
- ICML 2024Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
- ICML 2024Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
- ICML 2024Minimum Norm Interpolation Meets The Local Theory of Banach Spaces
- ICML 2024Model Alignment as Prospect Theoretic Optimization
- ICML 2024No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
- ICML 2024Non-convex Stochastic Composite Optimization with Polyak Momentum
- ICML 2024Non-stationary Online Convex Optimization with Arbitrary Delays
- ICML 2024On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization
- ICML 2024On Statistical Learning Theory for Distributional Inputs
- ICML 2024On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
- ICML 2024On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
- ICML 2024On the Last-Iterate Convergence of Shuffling Gradient Methods
- ICML 2024Open Ad Hoc Teamwork with Cooperative Game Theory
- ICML 2024Optimization without Retraction on the Random Generalized Stiefel Manifold
- ICML 2024PIDformer: Transformer Meets Control Theory
- ICML 2024Plug-in Performative Optimization
- ICML 2024Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
- ICML 2024Position: Future Directions in the Theory of Graph Machine Learning
- ICML 2024Position: Optimization in SciML Should Employ the Function Space Geometry
- ICML 2024Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory
- ICML 2024Principled Preferential Bayesian Optimization
- ICML 2024Proactive DP: A Multiple Target Optimization Framework for DP-SGD
- ICML 2024Quantum Algorithm for Online Exp-concave Optimization
- ICML 2024Random matrix theory improved Fréchet mean of symmetric positive definite matrices
- ICML 2024Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective
- ICML 2024Risk Aware Benchmarking of Large Language Models
- ICML 2024Robust Data-driven Prescriptiveness Optimization
- ICML 2024Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
- ICML 2024Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
- ICML 2024Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
- ICML 2024Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
- ICML 2024The Max-Min Formulation of Multi-Objective Reinforcement Learning: From Theory to a Model-Free Algorithm
- ICML 2024Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
- ICML 2024Transformers Get Stable: An End-to-End Signal Propagation Theory for Language Models
- ICML 2024Tuning-Free Stochastic Optimization
- ICML 2024Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data
- ICML 2024Universal Gradient Methods for Stochastic Convex Optimization
- ICML 2024Vanilla Bayesian Optimization Performs Great in High Dimensions
- NeurIPS 2024$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
- NeurIPS 20244+3 Phases of Compute-Optimal Neural Scaling Laws
- NeurIPS 2024A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
- NeurIPS 2024A Framework for Bilevel Optimization on Riemannian Manifolds
- NeurIPS 2024A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization
- NeurIPS 2024A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
- NeurIPS 2024A robust inlier identification algorithm for point cloud registration via $\mathbf{\ell_0}$-minimization
- NeurIPS 2024A two-scale Complexity Measure for Deep Learning Models
- NeurIPS 2024Accelerating Matroid Optimization through Fast Imprecise Oracles
- NeurIPS 2024Accelerating Non-Maximum Suppression: A Graph Theory Perspective
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。