通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026

主要结论

• 通用机器学习 · unsupervised and semisupervised learning论文从 2023 年的 649 篇增长到 2026 年的 799 篇，三年间扩大到约 1.2 倍。
• ICML 是发通用机器学习 · unsupervised and semisupervised learning论文最多的会议，2023–2026 年共 859 篇，占四个会议总量的 32%。
• 交叉方向里涨得最快的是深度学习 · self supervised learning：同时属于两个主题的论文从 2023 年的 23 篇增至 2026 年的 86 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 1；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · unsupervised and semisupervised learning是 1.2 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 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
• ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
• ICLR 2026A Generalized Geometric Theoretical Framework of Centroid Discriminant Analysis for Linear Classification of Multi-dimensional Data
• CVPR 2026COG Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object
• NeurIPS 2025$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
• ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
• ICLR 2025A General Framework for Producing Interpretable Semantic Text Embeddings
• CVPR 2025A General Adaptive Dual-level Weighting Mechanism for Remote Sensing Pansharpening
• NeurIPS 2024GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
• ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Dual Prototype Attention for Unsupervised Video Object Segmentation
• NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
• ICML 2023A Mathematical Model for Curriculum Learning for Parities
• ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
• CVPR 2023A General Regret Bound of Preconditioned Gradient Method for DNN Training
• NeurIPS 2026Attention-based PCA
• ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026CROWn A Unified Framework for Anti-Aliased Downsampling and Phase-Calibrated Fusion

全部通用机器学习 · unsupervised and semisupervised learning论文

共 157 篇，第 3 / 4 页

101. ICML 2023Offline Learning in Markov Games with General Function Approximation
102. ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
103. ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
104. ICML 2023On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs
105. ICML 2023On the Privacy-Robustness-Utility Trilemma in Distributed Learning
106. ICML 2023Optimal Arms Identification with Knapsacks
107. ICML 2023Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
108. ICML 2023Optimal Sets and Solution Paths of ReLU Networks
109. ICML 2023PaLM-E: An Embodied Multimodal Language Model
110. ICML 2023Parallel Neurosymbolic Integration with Concordia
111. ICML 2023Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach
112. ICML 2023Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
113. ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
114. ICML 2023Principled Acceleration of Iterative Numerical Methods Using Machine Learning
115. ICML 2023Prototype-oriented unsupervised anomaly detection for multivariate time series
116. ICML 2023Provably and Practically Efficient Neural Contextual Bandits
117. ICML 2023Provably Invariant Learning without Domain Information
118. ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
119. ICML 2023Random Teachers are Good Teachers
120. ICML 2023Regret Minimization and Convergence to Equilibria in General-sum Markov Games
121. ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
122. ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
123. ICML 2023Rethinking Backdoor Attacks
124. ICML 2023Rethinking Weak Supervision in Helping Contrastive Learning
125. ICML 2023Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
126. ICML 2023Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees
127. ICML 2023Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
128. ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
129. ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch
130. ICML 2023Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
131. ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
132. ICML 2023Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
133. ICML 2023Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation
134. ICML 2023Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
135. ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
136. ICML 2023Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
137. ICML 2023Sharper Bounds for $\ell_p$ Sensitivity Sampling
138. ICML 2023SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
139. ICML 2023SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
140. ICML 2023Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning
141. ICML 2023State and parameter learning with PARIS particle Gibbs
142. ICML 2023STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
143. ICML 2023Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems
144. ICML 2023The Edge of Orthogonality: A Simple View of What Makes BYOL Tick
145. ICML 2023Theory on Forgetting and Generalization of Continual Learning
146. ICML 2023Toward Large Kernel Models
147. ICML 2023Towards Understanding Generalization of Macro-AUC in Multi-label Learning
148. ICML 2023Transformers as Algorithms: Generalization and Stability in In-context Learning
149. ICML 2023UMD: Unsupervised Model Detection for X2X Backdoor Attacks
150. ICML 2023Underspecification Presents Challenges for Credibility in Modern Machine Learning

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

共 2,683 篇，按年份分别是 2023 年 649 篇、2024 年 553 篇、2025 年 682 篇、2026 年 799 篇。

NeurIPS 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

NeurIPS 2026 有 194 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 203 篇。

ICLR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

ICLR 2026 有 187 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 174 篇。

ICML 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

ICML 2026 有 348 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 239 篇。

CVPR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

CVPR 2026 有 70 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 66 篇。

哪个会议的通用机器学习 · unsupervised and semisupervised learning论文最多？

ICML，2023–2026 年共 859 篇。