通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026
通用机器学习：unsupervised_and_semisupervised_learning
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 2,683 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
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 649 篇，第 6 / 13 页
- ICML 2023Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
- ICML 2023Learning Control-Oriented Dynamical Structure from Data
- ICML 2023Learning Distributions over Quantum Measurement Outcomes
- ICML 2023Learning Rate Schedules in the Presence of Distribution Shift
- ICML 2023Learning Representations without Compositional Assumptions
- ICML 2023Learning to Boost Training by Periodic Nowcasting Near Future Weights
- ICML 2023Learning to Initiate and Reason in Event-Driven Cascading Processes
- ICML 2023Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
- ICML 2023Learning useful representations for shifting tasks and distributions
- ICML 2023Learning-Rate-Free Learning by D-Adaptation
- ICML 2023Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
- ICML 2023Lower Bounds for Learning in Revealing POMDPs
- ICML 2023Machine Learning Force Fields with Data Cost Aware Training
- ICML 2023Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
- ICML 2023Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming
- ICML 2023Mixture Proportion Estimation Beyond Irreducibility
- ICML 2023Model-Aware Contrastive Learning: Towards Escaping the Dilemmas
- ICML 2023Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
- ICML 2023Multiply Robust Off-policy Evaluation and Learning under Truncation by Death
- ICML 2023Near-Optimal $\Phi$-Regret Learning in Extensive-Form Games
- ICML 2023No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation
- ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
- ICML 2023Nonparametric Iterative Machine Teaching
- ICML 2023NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
- ICML 2023Offline Learning in Markov Games with General Function Approximation
- ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
- ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
- ICML 2023On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs
- ICML 2023On the Privacy-Robustness-Utility Trilemma in Distributed Learning
- ICML 2023Optimal Arms Identification with Knapsacks
- ICML 2023Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
- ICML 2023Optimal Sets and Solution Paths of ReLU Networks
- ICML 2023PaLM-E: An Embodied Multimodal Language Model
- ICML 2023Parallel Neurosymbolic Integration with Concordia
- ICML 2023Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach
- ICML 2023Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
- ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
- ICML 2023Principled Acceleration of Iterative Numerical Methods Using Machine Learning
- ICML 2023Prototype-oriented unsupervised anomaly detection for multivariate time series
- ICML 2023Provably and Practically Efficient Neural Contextual Bandits
- ICML 2023Provably Invariant Learning without Domain Information
- ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
- ICML 2023Random Teachers are Good Teachers
- ICML 2023Regret Minimization and Convergence to Equilibria in General-sum Markov Games
- ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
- ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
- ICML 2023Rethinking Backdoor Attacks
- ICML 2023Rethinking Weak Supervision in Helping Contrastive Learning
- ICML 2023Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
- ICML 2023Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees
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 查通用机器学习 · unsupervised and semisupervised learning在 ICML 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": "gml-unsupervised-and-semisupervised-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。