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
- 非凸优化论文从 2023 年的 346 篇增长到 2026 年的 757 篇,三年间扩大到约 2.2 倍。
- NeurIPS 是发非凸优化论文最多的会议,2023–2026 年共 958 篇,占四个会议总量的 41%。
- 交叉方向里涨得最快的是扩散模型:同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 44 篇。
- 在「优化与缩放」的 5 个主题里,它的 2026 年论文数排第 2;同组增长最快的缩放定律是 4.1 倍,非凸优化是 2.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 154 | 79 | 98 | 15 | 346 |
| 2024 | 275 | 107 | 160 | 18 | 560 |
| 2025 | 279 | 177 | 192 | 19 | 667 |
| 2026 | 250 | 178 | 286 | 43 | 757 |
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 2026$\gamma$-weakly $\theta$-up-concavity: A Unified Framework for Non-Convex Optimization Beyond DR-Submodular and OSS Functions
- ICML 2026$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
- ICLR 2026Behavioral Embeddings of Programs: A Quasi-Dynamic Approach for Optimization Prediction
- CVPR 2026Coverage Optimization for Camera View Selection
- NeurIPS 2025Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
- ICML 2025A Bregman Proximal Viewpoint on Neural Operators
- ICLR 2025A Truncated Newton Method for Optimal Transport
- CVPR 2025Balanced Rate-Distortion Optimization in Learned Image Compression
- NeurIPS 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences
- ICML 2024A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
- ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
- CVPR 2024FaceCom: Towards High-fidelity 3D Facial Shape Completion via Optimization and Inpainting Guidance
- NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
- ICML 2023A Distribution Optimization Framework for Confidence Bounds of Risk Measures
- ICLR 2023A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta.
- CVPR 2023Attribute-Preserving Face Dataset Anonymization via Latent Code Optimization
- NeurIPS 2026A Doubly Smoothed Decentralized Stochastic Minimax Optimization Algorithm
- ICML 2026A Constrained Optimization Perspective of Unrolled Transformers
- ICLR 2026BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
- CVPR 2026Fully Decentralized Certified Unlearning
全部非凸优化论文
共 2,330 篇,第 14 / 47 页
- NeurIPS 2026On Lipschitz Explosion in Deep Neural Networks with Normalization: Consequences for Optimization and Robustness
- NeurIPS 2026On the Convergence of Multicalibration Gradient Boosting
- NeurIPS 2026On the Convergence of Success Conditioning for Policy Optimization
- NeurIPS 2026On the Last-Iterate Convergence of Clipped Gradient Methods
- NeurIPS 2026On the Sparsity of Direct Preference Optimization: Weight Disentanglement in the NTK Regime
- NeurIPS 2026Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
- NeurIPS 2026Online Min-Max Optimization: From Individual Regrets to Cumulative Saddle Points
- NeurIPS 2026Optimal Hidden-Target Learning for Online Inventory Optimization on General Convex Sets
- NeurIPS 2026Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms
- NeurIPS 2026Ordered Policy Optimization
- NeurIPS 2026Orthogonal Updates for the Win: Towards Accelerated Adaptive Minimax Optimization
- NeurIPS 2026PACE: Partial-state Amortized Constraint Editing for Neural Combinatorial Optimization
- NeurIPS 2026PACO: Partial-order-Augmented Continuous Optimization for Differentiable Causal Discovery
- NeurIPS 2026Pairwise AUC Optimization Needs Corrective Power: A Unified View
- NeurIPS 2026Parallel Computation Algorithms and Convergence Guarantees for Mean-Field Langevin Dynamics
- NeurIPS 2026ParetoM$^3$: Learning on the Pareto Set under Preference Guidance via Min-Max-Min Optimization
- NeurIPS 2026Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning
- NeurIPS 2026Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation
- NeurIPS 2026PISG: Constraint-Aligned Signal Amplification for Diffusion-Based Combinatorial Optimization
- NeurIPS 2026Policy Optimization in Tabular MDPs: Data-dependent Regret under Unknown Transitions
- NeurIPS 2026POME: Post Optimization Model Edit via Muon-Style Projection
- NeurIPS 2026Position: Lottery Tickets Do Not Explain Overparameterization. How About Escape Dimensions?
- NeurIPS 2026Posterior Alternative Calibration in Ambiguous Inverse Problems
- NeurIPS 2026Preference Conditioned Multi-Objective Reinforcement Learning: Decomposed, Diversity-Driven Policy Optimization
- NeurIPS 2026Principled Policy Optimization for LLMs via Self-Normalized Importance Sampling
- NeurIPS 2026Quality-Diversity Optimization as Multi-Objective Optimization
- NeurIPS 2026Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise
- NeurIPS 2026Randomized Kriging Believer For Parallel Bayesian Optimization With Regret Bounds
- NeurIPS 2026Rationale-Guided Policy Optimization: Learning to Reason with Adaptive Rationale Scaffolding
- NeurIPS 2026Rectified Policy Rollouts with Hierarchical Expert Guidance for Neural Combinatorial Optimization
- NeurIPS 2026Reflective Prompted Policy Optimization: Trajectory-Grounded Revision and Salience Bias
- NeurIPS 2026Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization
- NeurIPS 2026Regularization Paths for Continuous DAG Learning
- NeurIPS 2026Regularized Large Neighborhood Search
- NeurIPS 2026Reinforcement Learning for Code Optimization
- NeurIPS 2026Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
- NeurIPS 2026ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization
- NeurIPS 2026Rennala-NSGD: Asynchronous Stochastic Optimization Beyond Euclidean Geometry
- NeurIPS 2026Replay-buffer engineering for noise-robust quantum circuit optimization
- NeurIPS 2026RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models
- NeurIPS 2026Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity
- NeurIPS 2026Rethinking Bayesian Optimization for Co-Optimizing LLM Training Configurations
- NeurIPS 2026Rethinking Gradient Approximation in Quantization: A Zeroth-Order Expectation Perspective
- NeurIPS 2026Rethinking Language Model Scaling under Transferable Hypersphere Optimization
- NeurIPS 2026Revisiting Decentralized Online Convex Optimization with Compressed Communication
- NeurIPS 2026Riemannian Bilevel Optimization under the Polyak–Łojasiewicz Condition
- NeurIPS 2026Riemannian Lyapunov Framework: Optimization as Closed-Loop Control on Riemannian Manifolds
- NeurIPS 2026Robust Inference-Time Steering of Protein Diffusion Models via Embedding Optimization
- NeurIPS 2026Robust Latent Space Bayesian Optimization with Marginalized Kernel
- NeurIPS 2026Robust Noisy Inductive Matrix Completion with Local Linear Convergence
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"}
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。