深度学习 · optimization论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：optimization
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 953 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 144 | 34 | 70 | 8 | 256 |
| 2024 | 191 | 30 | 72 | 1 | 294 |
| 2025 | 62 | 51 | 44 | 6 | 163 |
| 2026 | 103 | 44 | 86 | 7 | 240 |
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 240 篇，第 5 / 5 页
- NeurIPS 2026Optimization Dynamics Imprint Semantic Specificity in Contrastive Embedding Norms
- NeurIPS 2026Orthogonal Updates for the Win: Towards Accelerated Adaptive Minimax Optimization
- NeurIPS 2026PACE: Partial-state Amortized Constraint Editing for Neural Combinatorial Optimization
- NeurIPS 2026Pairwise AUC Optimization Needs Corrective Power: A Unified View
- NeurIPS 2026ParetoM$^3$: Learning on the Pareto Set under Preference Guidance via Min-Max-Min Optimization
- NeurIPS 2026Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs
- NeurIPS 2026POME: Post Optimization Model Edit via Muon-Style Projection
- NeurIPS 2026Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise
- NeurIPS 2026Randomized Kriging Believer For Parallel Bayesian Optimization With Regret Bounds
- NeurIPS 2026Regret-Based $(\epsilon,\delta)$-optimal Stopping Criteria for Bayesian Optimization
- NeurIPS 2026Regularization Paths for Continuous DAG Learning
- NeurIPS 2026Regularized Large Neighborhood Search
- NeurIPS 2026Rennala-NSGD: Asynchronous Stochastic Optimization Beyond Euclidean Geometry
- 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 Latent Space Bayesian Optimization with Marginalized Kernel
- NeurIPS 2026Route-Consistent Adaptation for Stable Quantization of Mixture-of-Experts Models with Theoretical Guarantees
- NeurIPS 2026Sample complexity of stochastic optimization with integer variables
- NeurIPS 2026SAS: Simple Attention Sparsification via End-to-End Optimization of Context Ranking
- NeurIPS 2026Select-then-differentiate: Solving Bilevel Optimization with Manifold Lower-level Solution Sets
- NeurIPS 2026Sharper Guarantees for Misspecified Kernelized Bandit Optimization
- NeurIPS 2026Sign-Based Optimizers Are Effective Under Heavy-Tailed Noise
- NeurIPS 2026Skip the Hessian, Keep the Rates: Globalized Semismooth Newton with Lazy Hessian Updates
- NeurIPS 2026Solving Max-Cut to Global Optimality via Feasibility-Preserving Graph Neural Networks
- NeurIPS 2026Spectral Annealing: Normalization-Path Exploration for Large-Scale Ising Optimization
- NeurIPS 2026Stochastic Approximation Approach for Decentralized Optimization on Time Varying Random Networks
- NeurIPS 2026Stochastic Dynamic Barrier Perturbed Gradient Methods for Nonconvex Simple Bilevel Optimization
- NeurIPS 2026Stochastic Reconfiguration as Statistical Filtering for Overparameterized Neural Quantum States
- NeurIPS 2026Stochastic Zeroth-Order Optimization Under Heavy-Tailed Noise
- NeurIPS 2026Structure vs. Chaos: Asymmetric Entropic Optimization for Enforcing Instruction Hierarchy
- NeurIPS 2026Taming the Tails: Why Distributionally Robust Optimization Needs New Theory for Imbalanced Regression
- NeurIPS 2026The Cost of Mismatch: Noise Amplification in Zeroth-Order Reinforcement Learning
- NeurIPS 2026The Optimization Prior: Instilling depth for shallow networks, detail for coarse networks
- NeurIPS 2026Towards Hyperparameter Transfer for Differentially Private Optimization
- NeurIPS 2026Towards Settling the Complexity of Non-Euclidean Parallel Convex Optimization
- NeurIPS 2026Truncated Riemannian (1+1)-ES for Black-Box Optimization with Intrinsic Dimension Guarantees
- NeurIPS 2026Why Pass@k Optimization Can Degrade Pass@1: Prompt Interference in LLM Post-Training
- NeurIPS 2026Your Hypergradient is Skewed: Antithetic Neumann Estimation for Bilevel Optimization
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 查深度学习 · 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": "dl-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。
「深度学习」下的其他主题
- 扩散模型 6,900
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · graph neural networks 1,648
- 深度学习 · representation learning 802
- 深度学习 · probabilistic methods 637
- 深度学习 · foundation models 536
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197