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 154 篇,第 1 / 4 页
- NeurIPS 2023(Amplified) Banded Matrix Factorization: A unified approach to private training
- NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
- NeurIPS 20232Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression
- NeurIPS 2023A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
- NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
- NeurIPS 2023A Finite-Particle Convergence Rate for Stein Variational Gradient Descent
- NeurIPS 2023A Single-Loop Accelerated Extra-Gradient Difference Algorithm with Improved Complexity Bounds for Constrained Minimax Optimization
- NeurIPS 2023A Unified Approach for Maximizing Continuous DR-submodular Functions
- NeurIPS 2023A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
- NeurIPS 2023A Unified Framework for Rank-based Loss Minimization
- NeurIPS 2023Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization
- NeurIPS 2023Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
- NeurIPS 2023Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
- NeurIPS 2023Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction
- NeurIPS 2023Advancing Bayesian Optimization via Learning Correlated Latent Space
- NeurIPS 2023An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
- NeurIPS 2023An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits
- NeurIPS 2023An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
- NeurIPS 2023An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions
- NeurIPS 2023AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
- NeurIPS 2023Batch Bayesian Optimization For Replicable Experimental Design
- NeurIPS 2023Bias in Evaluation Processes: An Optimization-Based Model
- NeurIPS 2023Bicriteria Approximation Algorithms for the Submodular Cover Problem
- NeurIPS 2023Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start
- NeurIPS 2023BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization
- NeurIPS 2023Block Coordinate Plug-and-Play Methods for Blind Inverse Problems
- NeurIPS 2023Boosting with Tempered Exponential Measures
- NeurIPS 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
- NeurIPS 2023Cascading Contextual Assortment Bandits
- NeurIPS 2023Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
- NeurIPS 2023Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control
- NeurIPS 2023Contextual Stochastic Bilevel Optimization
- NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
- NeurIPS 2023Convergence of Adam Under Relaxed Assumptions
- NeurIPS 2023Convergence of Alternating Gradient Descent for Matrix Factorization
- NeurIPS 2023Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
- NeurIPS 2023Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems
- NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
- NeurIPS 2023CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
- NeurIPS 2023Debiasing Conditional Stochastic Optimization
- NeurIPS 2023Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence
- NeurIPS 2023Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization
- NeurIPS 2023Distributionally Robust Bayesian Optimization with $\varphi$-divergences
- NeurIPS 2023Distributionally Robust Linear Quadratic Control
- NeurIPS 2023Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models
- NeurIPS 2023Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
- NeurIPS 2023DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework
- NeurIPS 2023DropCompute: simple and more robust distributed synchronous training via compute variance reduction
- NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
- NeurIPS 2023Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs
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。