深度学习 · optimization论文趋势 2023–2026

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。

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 144 篇，第 3 / 3 页

101. NeurIPS 2023Parallel Submodular Function Minimization
102. NeurIPS 2023Parallel-mentoring for Offline Model-based Optimization
103. NeurIPS 2023Path following algorithms for $\ell_2$-regularized $M$-estimation with approximation guarantee
104. NeurIPS 2023Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
105. NeurIPS 2023Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games
106. NeurIPS 2023Percentile Criterion Optimization in Offline Reinforcement Learning
107. NeurIPS 2023Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width
108. NeurIPS 2023Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control
109. NeurIPS 2023Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
110. NeurIPS 2023Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
111. NeurIPS 2023Predict-then-Calibrate: A New Perspective of Robust Contextual LP
112. NeurIPS 2023PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
113. NeurIPS 2023Projection-Free Online Convex Optimization via Efficient Newton Iterations
114. NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
115. NeurIPS 2023Quantum Bayesian Optimization
116. NeurIPS 2023Quantum speedups for stochastic optimization
117. NeurIPS 2023Reduced Policy Optimization for Continuous Control with Hard Constraints
118. NeurIPS 2023Regret Minimization via Saddle Point Optimization
119. NeurIPS 2023Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions
120. NeurIPS 2023Resetting the Optimizer in Deep RL: An Empirical Study
121. NeurIPS 2023ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
122. NeurIPS 2023Revisiting Implicit Differentiation for Learning Problems in Optimal Control
123. NeurIPS 2023Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
124. NeurIPS 2023Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
125. NeurIPS 2023Riemannian stochastic optimization methods avoid strict saddle points
126. NeurIPS 2023Robust Learning for Smoothed Online Convex Optimization with Feedback Delay
127. NeurIPS 2023Sampling weights of deep neural networks
128. NeurIPS 2023Self-Correcting Bayesian Optimization through Bayesian Active Learning
129. NeurIPS 2023SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
130. NeurIPS 2023Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions
131. NeurIPS 2023SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization
132. NeurIPS 2023Solving a Class of Non-Convex Minimax Optimization in Federated Learning
133. NeurIPS 2023SpatialRank: Urban Event Ranking with NDCG Optimization on Spatiotemporal Data
134. NeurIPS 2023State Regularized Policy Optimization on Data with Dynamics Shift
135. NeurIPS 2023Stochastic Approximation Approaches to Group Distributionally Robust Optimization
136. NeurIPS 2023TD Convergence: An Optimization Perspective
137. NeurIPS 2023Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
138. NeurIPS 2023Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints
139. NeurIPS 2023Understanding Contrastive Learning via Distributionally Robust Optimization
140. NeurIPS 2023Universal Gradient Descent Ascent Method for Nonconvex-Nonconcave Minimax Optimization
141. NeurIPS 2023Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization
142. NeurIPS 2023Weitzman's Rule for Pandora's Box with Correlations
143. NeurIPS 2023When Does Optimizing a Proper Loss Yield Calibration?
144. NeurIPS 2023Winner Takes It All: Training Performant RL Populations for Combinatorial 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。