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 115 篇，第 1 / 3 页

1. ICML 2024A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
2. ICML 2024A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
3. ICML 2024A General Framework for Learning from Weak Supervision
4. ICML 2024A General Framework for Sequential Decision-Making under Adaptivity Constraints
5. ICML 2024A General Online Algorithm for Optimizing Complex Performance Metrics
6. ICML 2024A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
7. ICML 2024A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
8. ICML 2024A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation
9. ICML 2024A3S: A General Active Clustering Method with Pairwise Constraints
10. ICML 2024Agent Instructs Large Language Models to be General Zero-Shot Reasoners
11. ICML 2024Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms
12. ICML 2024Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms
13. ICML 2024Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
14. ICML 2024An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
15. ICML 2024An Unsupervised Approach for Periodic Source Detection in Time Series
16. ICML 2024Averaging $n$-step Returns Reduces Variance in Reinforcement Learning
17. ICML 2024Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
18. ICML 2024Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium
19. ICML 2024Causal Representation Learning from Multiple Distributions: A General Setting
20. ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
21. ICML 2024Collaborative Learning with Different Labeling Functions
22. ICML 2024Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth
23. ICML 2024Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
24. ICML 2024Constrained Ensemble Exploration for Unsupervised Skill Discovery
25. ICML 2024Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms
26. ICML 2024Convergence of Some Convex Message Passing Algorithms to a Fixed Point
27. ICML 2024convSeq: Fast and Scalable Method for Detecting Patterns in Spike Data
28. ICML 2024Debating with More Persuasive LLMs Leads to More Truthful Answers
29. ICML 2024DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
30. ICML 2024Discovering Bias in Latent Space: An Unsupervised Debiasing Approach
31. ICML 2024Disentanglement Learning via Topology
32. ICML 2024Do Efficient Transformers Really Save Computation?
33. ICML 2024Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods
34. ICML 2024Dynamic Facility Location in High Dimensional Euclidean Spaces
35. ICML 2024EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
36. ICML 2024Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
37. ICML 2024Estimating Barycenters of Distributions with Neural Optimal Transport
38. ICML 2024Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
39. ICML 2024Faster Sampling via Stochastic Gradient Proximal Sampler
40. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
41. ICML 2024Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
42. ICML 2024Generalization Analysis of Stochastic Weight Averaging with General Sampling
43. ICML 2024GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
44. ICML 2024GNNs Also Deserve Editing, and They Need It More Than Once
45. ICML 2024How Flawed Is ECE? An Analysis via Logit Smoothing
46. ICML 2024Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
47. ICML 2024IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
48. ICML 2024Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
49. ICML 2024Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
50. ICML 2024Improving Diffusion Models for Inverse Problems Using Optimal Posterior Covariance

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。