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 2,682 篇，第 28 / 54 页
- NeurIPS 2025Flatness is Necessary, Neural Collapse is Not: Rethinking Generalization via Grokking
- NeurIPS 2025Flux4D: Flow-based Unsupervised 4D Reconstruction
- NeurIPS 2025Fréchet Geodesic Boosting
- NeurIPS 2025Generalization Guarantees for Learning Score-Based Branch-and-Cut Policies in Integer Programming
- NeurIPS 2025Generalizing while preserving monotonicity in comparison-based preference learning models
- NeurIPS 2025GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers
- NeurIPS 2025Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration
- NeurIPS 2025Graph–Smoothed Bayesian Black-Box Shift Estimator and Its Information Geometry
- NeurIPS 2025Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe
- NeurIPS 2025How many measurements are enough? Bayesian recovery in inverse problems with general distributions
- NeurIPS 2025Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering
- NeurIPS 2025IA-GGAD: Zero-shot Generalist Graph Anomaly Detection via Invariant and Affinity Learning
- NeurIPS 2025Imbalances in Neurosymbolic Learning: Characterization and Mitigating Strategies
- NeurIPS 2025Implicit Bias of Spectral Descent and Muon on Multiclass Separable Data
- NeurIPS 2025Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach
- NeurIPS 2025Improved Confidence Regions and Optimal Algorithms for Online and Offline Linear MNL Bandits
- NeurIPS 2025Improving Regret Approximation for Unsupervised Dynamic Environment Generation
- NeurIPS 2025Improving Task-Specific Multimodal Sentiment Analysis with General MLLMs via Prompting
- NeurIPS 2025Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
- NeurIPS 2025Incomplete Multi-view Clustering via Hierarchical Semantic Alignment and Cooperative Completion
- NeurIPS 2025Incomplete Multi-view Deep Clustering with Data Imputation and Alignment
- NeurIPS 2025Interactive and Hybrid Imitation Learning: Provably Beating Behavior Cloning
- NeurIPS 2025Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
- NeurIPS 2025KAIROS: Scalable Model-Agnostic Data Valuation
- NeurIPS 2025KSP: Kolmogorov-Smirnov metric-based Post-Hoc Calibration for Survival Analysis
- NeurIPS 2025Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification
- NeurIPS 2025Learning single index models via harmonic decomposition
- NeurIPS 2025Learning to Learn with Contrastive Meta-Objective
- NeurIPS 2025Learning with Restricted Boltzmann Machines: Asymptotics of AMP and GD in High Dimensions
- NeurIPS 2025Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
- NeurIPS 2025LLM Meeting Decision Trees on Tabular Data
- NeurIPS 2025Localized Data Shapley: Accelerating Valuation for Nearest Neighbor Algorithms
- NeurIPS 2025Long-tailed Recognition with Model Rebalancing
- NeurIPS 2025Looking Into the Water by Unsupervised Learning of the Surface Shape
- NeurIPS 2025LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
- NeurIPS 2025Luminance-Aware Statistical Quantization: Unsupervised Hierarchical Learning for Illumination Enhancement
- NeurIPS 2025MAP Estimation with Denoisers: Convergence Rates and Guarantees
- NeurIPS 2025Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
- NeurIPS 2025MetaSlot: Break Through the Fixed Number of Slots in Object-Centric Learning
- NeurIPS 2025Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
- NeurIPS 2025Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning
- NeurIPS 2025Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
- NeurIPS 2025Multiresolution Analysis and Statistical Thresholding on Dynamic Networks
- NeurIPS 2025Nearly-Linear Time and Massively Parallel Algorithms for $k$-anonymity
- NeurIPS 2025Neural Fractional Attention Differential Equations
- NeurIPS 2025Neural Mutual Information Estimation with Vector Copulas
- NeurIPS 2025Neural Networks for Learnable and Scalable Influence Estimation of Instruction Fine-Tuning Data
- NeurIPS 2025Non-exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shift with Unlabeled Data
- NeurIPS 2025OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction
- NeurIPS 2025On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning
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。