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 833 篇，第 4 / 17 页
- NeurIPS 2026SemGeo-Gen: Unsupervised Generation of Approximate Cross-Instance Semantic-Geometric Correspondences
- NeurIPS 2026Settling Pure Differentially Private Covariance Estimation
- NeurIPS 2026ShiftRAG: Bypassing the Textual Bottleneck via Decoupled Learning and Continuous Soft Tokens
- NeurIPS 2026Simulation-free Unbalanced Dynamic Optimal Transport with General Growth Penalty
- NeurIPS 2026Sparse Koopman Autoencoders Identify Local Dynamical Regimes in Multibasin Systems
- NeurIPS 2026Sparsifying Correlation Clustering: Edge Coresets, Triangle Witnesses, and Observation Lower Bounds
- NeurIPS 2026SPATIALEPIBENCH: Benchmarking Spatial Information and Epidemic Priors in Forecasting
- NeurIPS 2026State-Action Selection in General Stochastic Games under Regularized Policy Gradient Methods
- NeurIPS 2026State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives
- NeurIPS 2026Subdata Selection: A Unified Framework for Optimal Selection and Statistical Efficiency Assessment
- NeurIPS 2026Submodular Benchmark Selection
- NeurIPS 2026Subspace-Guided Continual Learning: Hessian Based Stable–Plastic Decomposition for Exemplar-Free Class-Incremental Learning
- NeurIPS 2026Symmetry Guarantees Statistic Recovery in Variational Inference
- NeurIPS 2026Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data
- NeurIPS 2026TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering
- NeurIPS 2026TabK: Amortized Bayesian Estimation of the Number of Clusters in Tabular Data
- NeurIPS 2026TENET: Time-point Encoding Network for Multivariate Time Series Anomaly Detection
- NeurIPS 2026Testable Learning of General Halfspaces under Massart Noise
- NeurIPS 2026The BV4 Benchmark for Unsupervised Anomaly Detection in High-Dimensional Spectral Data Streams
- NeurIPS 2026The parameters in weight-sparse transformers are interpretable
- NeurIPS 2026The Query Complexity of Local Search in Rounds on General Graphs
- NeurIPS 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
- NeurIPS 2026The Sampling Complexity of Condorcet Winner Identification in Dueling Bandits
- NeurIPS 2026TILT: Target-induced loss tilting under covariate shift
- NeurIPS 2026ToMAToMP: Robust and Multi-Parameter Topological Clustering
- NeurIPS 2026TopoPrune: Robust Data Pruning via Unified Latent Space Topology
- NeurIPS 2026Towards Identifiable Latent Additive Noise Models
- NeurIPS 2026Towards more general control of diffusion models using Jeffrey Guidance
- NeurIPS 2026Towards Understanding the Power and Limits of the Muon Optimizer: A River-Valley Perspective
- NeurIPS 2026Tracing Actual Causes with Counterfactual Witness Maps
- NeurIPS 2026Tree Search With Predictions
- NeurIPS 2026Trust Region Continual Learning as an Implicit Meta-Learner
- NeurIPS 2026UGGRH: Unsupervised Generative Completion and Graph-attention Refinement for Incomplete Cross-modal Hashing
- NeurIPS 2026UniRAP: Towards Unified Part-level Physical Affordance Reasoning and Actionable Perception
- NeurIPS 2026Unpaired Canonical Correlation Analysis
- NeurIPS 2026Unrolled gradients in disguise: bridging interpolation-based and Jacobian regularization for stable neural dynamics
- NeurIPS 2026Unsupervised Concept Discovery with Dirichlet Concept Diffusion Models
- NeurIPS 2026Virtual-Flow: Virtual Microphone-based Speech Enhancement via Unsupervised Flow Matching
- NeurIPS 2026What the Geometry of Good Models Tells Us
- NeurIPS 2026What Transformer FFNs Never See: Theory, Diagnosis, and Lightweight Remediation
- NeurIPS 2026When and Why is Optimistic Multiplicative Weights Slow? The Geometry of Energy Dissipation
- NeurIPS 2026Words That Make Language Models Perceive
- NeurIPS 2026You Don’t Need Aligned Representations: Knowledge Distillation via Random Prototype Spaces
- NeurIPS 2026Your Embedding Model Is SMARTer Than You Think
- NeurIPS 2025$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
- NeurIPS 2025A Bayesian Approach to Contextual Dynamic Pricing using the Proportional Hazards Model with Discrete Price Data
- NeurIPS 2025A Closer Look to Positive-Unlabeled Learning from Fine-grained Perspectives: An Empirical Study
- NeurIPS 2025A faster training algorithm for regression trees with linear leaves, and an analysis of its complexity
- NeurIPS 2025A Few Moments Please: Scalable Graphon Learning via Moment Matching
- NeurIPS 2025A General-Purpose Theorem for High-Probability Bounds of Stochastic Approximation with Polyak Averaging
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。