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 348 篇，第 6 / 7 页
- ICML 2026Remove the Ambiguity: Few-shot Multimodal Anomaly Detection Using Crossmodal Feature Replacers
- ICML 2026Resilient Coresets and Clustering
- ICML 2026Rethinking Loss Reweighting for Imbalance Learning as an Inverse Problem: A Neural Collapse Point of View
- ICML 2026Rethinking Sparse Mixture of Experts from a Unified Perspective
- ICML 2026Return of Frustratingly Easy Unsupervised Video Domain Adaptation
- ICML 2026Revisiting the Platonic Representation Hypothesis: An Aristotelian View
- ICML 2026Revisiting the Role of Pretrained Weights in Model Merging: On Near-Optimality within the Core Subspace
- ICML 2026Robust and Consistent Ski Rental with Distributional Advice
- ICML 2026Robust Signal Enhancement via Fractional Detail Views and Knowledge Guided Multi-view Fusion
- ICML 2026SC-FAGC: Size Constrained Fast Anchor-based Graph Clustering
- ICML 2026Scalable and Interpretable Representation Alignment with Ordinal Similarity
- ICML 2026Scale-Aware Domain Harmonization for Domain Adaptation Person Search
- ICML 2026Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization
- ICML 2026Score-Repellent Monte Carlo: Toward Efficient Non-Markovian Sampler with Constant Memory in General State Spaces
- ICML 2026ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
- ICML 2026SE(n)-Invariant Flow Matching: A General Framework with Application to Object Reassembly
- ICML 2026See, Act, Adapt: Active Perception for Unsupervised Cross-Domain Visual Adaptation via Personalized VLM-Guided Agent
- ICML 2026Semi-Supervised Gaze Estimation via Disentangled Subspace Contrastive Learning
- ICML 2026Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus
- ICML 2026Semi-Supervised Learning with Noisy Proxy Covariates: Generalization Bounds and Distribution Regression
- ICML 2026Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer
- ICML 2026Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?
- ICML 2026Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms
- ICML 2026Sharp Inequalities between Total Variation and Hellinger Distances for Gaussian Mixtures
- ICML 2026SIMPC: Learning Self-Induced Mirror-Point Consistency for Unsupervised Point Cloud Denoising
- ICML 2026Sinkhorn Normalization of Diffusion Kernels
- ICML 2026Sketch-Based Low-Rank Model Merging with Shared Circulant Transforms
- ICML 2026SlaClip: Gradient Norm Slacks can be Indicator for Adaptive Clipping in DP-SGD
- ICML 2026SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity
- ICML 2026Solving Time-Dependent Differential Equations with Physical Dynamical Systems
- ICML 2026Source-Free Open-World RF Fingerprint Identification
- ICML 2026SpatioLM: Towards General Physical Spatial Intelligence in Vision-Language Models
- ICML 2026Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
- ICML 2026Stabilizing Equation Learning via Zero-Point Constraints
- ICML 2026Steady-State Behavior of Constant-Stepsize Stochastic Approximation: Gaussian Approximation and Tail Bounds
- ICML 2026Stochastic Linear Bandits with Parameter Noise
- ICML 2026Streaming Sliced Optimal Transport
- ICML 2026Subliminal Effects in Your Data: A General Mechanism via Log-Linearity
- ICML 2026SURF: Separation via Unsupervised Remixing Flow
- ICML 2026Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection
- ICML 2026Temper-Then-Tilt: Principled Unlearning for Generative Models through Tempering and Classifier Guidance
- ICML 2026Temporal Preference Optimization for Unsupervised Retrieval
- ICML 2026The Accumulation of Score Estimation Error in Diffusion Models
- ICML 2026The ACUTE Protocol: Operationalizing Language Model Activations for Better Calibration, Utility, and Trust
- ICML 2026The benefits of full data shuffle, now with optimal I/O cost: $k$-wise independence and matrix transposition to the rescue
- ICML 2026The Consistency Dilemma in LLMs: Generator-Evaluator Agreement and Vulnerability to Mistakes
- ICML 2026The Cost of Information: Phase Transitions in Contextual Bandits with Paid Observations
- ICML 2026The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning
- ICML 2026The Relative Instability of Model Comparison with Cross-validation
- ICML 2026Theoretical Investigation on Inductive Bias of Isolation Forest
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。