通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026

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。

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 157 篇，第 1 / 4 页

1. ICML 2023A General Representation Learning Framework with Generalization Performance Guarantees
2. ICML 2023A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
3. ICML 2023A Mathematical Model for Curriculum Learning for Parities
4. ICML 2023A Model-Based Method for Minimizing CVaR and Beyond
5. ICML 2023A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
6. ICML 2023Adaptive Annealed Importance Sampling with Constant Rate Progress
7. ICML 2023Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions
8. ICML 2023Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
9. ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
10. ICML 2023Anchor Sampling for Federated Learning with Partial Client Participation
11. ICML 2023Are Equivariant Equilibrium Approximators Beneficial?
12. ICML 2023Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations
13. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
14. ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
15. ICML 2023AutoCoreset: An Automatic Practical Coreset Construction Framework
16. ICML 2023Behavior Contrastive Learning for Unsupervised Skill Discovery
17. ICML 2023Beyond the Edge of Stability via Two-step Gradient Updates
18. ICML 2023BiBench: Benchmarking and Analyzing Network Binarization
19. ICML 2023Calibrating Multimodal Learning
20. ICML 2023Can Neural Network Memorization Be Localized?
21. ICML 2023Cell-Free Latent Go-Explore
22. ICML 2023Certifying Ensembles: A General Certification Theory with S-Lipschitzness
23. ICML 2023CLUTR: Curriculum Learning via Unsupervised Task Representation Learning
24. ICML 2023Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis
25. ICML 2023CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
26. ICML 2023Combinatorial Neural Bandits
27. ICML 2023ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
28. ICML 2023Conditions and Assumptions for Constraint-based Causal Structure Learning
29. ICML 2023Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation
30. ICML 2023Continual Learners are Incremental Model Generalizers
31. ICML 2023Contrastive Learning Meets Homophily: Two Birds with One Stone
32. ICML 2023Controllability-Aware Unsupervised Skill Discovery
33. ICML 2023Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
34. ICML 2023Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
35. ICML 2023Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum
36. ICML 2023Deterministic equivalent and error universality of deep random features learning
37. ICML 2023Differentiable and Transportable Structure Learning
38. ICML 2023Dimensionality Reduction for General KDE Mode Finding
39. ICML 2023Discovering Object-Centric Generalized Value Functions From Pixels
40. ICML 2023Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark
41. ICML 2023DUET: 2D Structured and Approximately Equivariant Representations
42. ICML 2023Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
43. ICML 2023E$(n)$ Equivariant Message Passing Simplicial Networks
44. ICML 2023Effective Structured Prompting by Meta-Learning and Representative Verbalizer
45. ICML 2023Entropy-driven Unsupervised Keypoint Representation Learning in Videos
46. ICML 2023Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms
47. ICML 2023Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection
48. ICML 2023Evaluating Unsupervised Denoising Requires Unsupervised Metrics
49. ICML 2023Evidential Interactive Learning for Medical Image Captioning
50. ICML 2023FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels

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。