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 553 篇，第 7 / 12 页
- ICLR 2024Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach
- ICLR 2024Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
- ICLR 2024Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
- ICLR 2024Towards Meta-Pruning via Optimal Transport
- ICLR 2024Transferring Learning Trajectories of Neural Networks
- ICLR 2024Transformer Fusion with Optimal Transport
- ICLR 2024Transformers can optimally learn regression mixture models
- ICLR 2024Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
- ICLR 2024Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression
- ICLR 2024Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
- ICLR 2024Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
- ICLR 2024UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
- ICLR 2024Unsupervised Order Learning
- ICLR 2024Unsupervised Pretraining for Fact Verification by Language Model Distillation
- ICLR 2024Video Decomposition Prior: Editing Videos Layer by Layer
- ICLR 2024VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE
- ICLR 2024Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning
- ICLR 2024What does automatic differentiation compute for neural networks?
- ICLR 2024When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
- ICLR 2024Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs
- ICML 2024A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
- ICML 2024A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
- ICML 2024A General Framework for Learning from Weak Supervision
- ICML 2024A General Framework for Sequential Decision-Making under Adaptivity Constraints
- ICML 2024A General Online Algorithm for Optimizing Complex Performance Metrics
- ICML 2024A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
- ICML 2024A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
- ICML 2024A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation
- ICML 2024A3S: A General Active Clustering Method with Pairwise Constraints
- ICML 2024Agent Instructs Large Language Models to be General Zero-Shot Reasoners
- ICML 2024Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms
- ICML 2024Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms
- ICML 2024Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
- ICML 2024An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
- ICML 2024An Unsupervised Approach for Periodic Source Detection in Time Series
- ICML 2024Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
- ICML 2024Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
- ICML 2024Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
- ICML 2024Causal Representation Learning from Multiple Distributions: A General Setting
- ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
- ICML 2024Collaborative Learning with Different Labeling Functions
- ICML 2024Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth
- ICML 2024Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
- ICML 2024Constrained Ensemble Exploration for Unsupervised Skill Discovery
- ICML 2024Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms
- ICML 2024Convergence of Some Convex Message Passing Algorithms to a Fixed Point
- ICML 2024convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data
- ICML 2024Debating with More Persuasive LLMs Leads to More Truthful Answers
- ICML 2024DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
- ICML 2024Discovering Bias in Latent Space: An Unsupervised Debiasing Approach
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。