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 500 篇,第 10 / 10 页
- NeurIPS 2023Online Control for Meta-optimization
- NeurIPS 2023Online Convex Optimization with Unbounded Memory
- NeurIPS 2023Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization
- NeurIPS 2023Online Learning under Adversarial Nonlinear Constraints
- NeurIPS 2023Optimization of Inter-group criteria for clustering with minimum size constraints
- NeurIPS 2023Outlier-Robust Gromov-Wasserstein for Graph Data
- NeurIPS 2023Parallel Submodular Function Minimization
- NeurIPS 2023Parallel-mentoring for Offline Model-based Optimization
- NeurIPS 2023Path following algorithms for $\ell_2$-regularized $M$-estimation with approximation guarantee
- NeurIPS 2023Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
- NeurIPS 2023Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games
- NeurIPS 2023Percentile Criterion Optimization in Offline Reinforcement Learning
- NeurIPS 2023Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
- NeurIPS 2023Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
- NeurIPS 2023Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
- NeurIPS 2023Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
- NeurIPS 2023Predict-then-Calibrate: A New Perspective of Robust Contextual LP
- NeurIPS 2023PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
- NeurIPS 2023Projection-Free Online Convex Optimization via Efficient Newton Iterations
- NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
- NeurIPS 2023Quantum Bayesian Optimization
- NeurIPS 2023Quantum speedups for stochastic optimization
- NeurIPS 2023Reduced Policy Optimization for Continuous Control with Hard Constraints
- NeurIPS 2023Regret Minimization via Saddle Point Optimization
- NeurIPS 2023Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions
- NeurIPS 2023Resetting the Optimizer in Deep RL: An Empirical Study
- NeurIPS 2023ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
- NeurIPS 2023Revisiting Implicit Differentiation for Learning Problems in Optimal Control
- NeurIPS 2023Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
- NeurIPS 2023Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
- NeurIPS 2023Riemannian stochastic optimization methods avoid strict saddle points
- NeurIPS 2023Robust Learning for Smoothed Online Convex Optimization with Feedback Delay
- NeurIPS 2023Sampling weights of deep neural networks
- NeurIPS 2023Self-Correcting Bayesian Optimization through Bayesian Active Learning
- NeurIPS 2023SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
- NeurIPS 2023Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions
- NeurIPS 2023SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization
- NeurIPS 2023Solving a Class of Non-Convex Minimax Optimization in Federated Learning
- NeurIPS 2023SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data
- NeurIPS 2023State Regularized Policy Optimization on Data with Dynamics Shift
- NeurIPS 2023Stochastic Approximation Approaches to Group Distributionally Robust Optimization
- NeurIPS 2023TD Convergence: An Optimization Perspective
- NeurIPS 2023Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
- NeurIPS 2023Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints
- NeurIPS 2023Understanding Contrastive Learning via Distributionally Robust Optimization
- NeurIPS 2023Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization
- NeurIPS 2023Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization
- NeurIPS 2023Weitzman's Rule for Pandora's Box with Correlations
- NeurIPS 2023When Does Optimizing a Proper Loss Yield Calibration?
- NeurIPS 2023Winner Takes It All: Training Performant RL Populations for Combinatorial 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