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 187 篇，第 2 / 4 页

51. ICLR 2026Differentiable Lifting for Topological Neural Networks
52. ICLR 2026Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
53. ICLR 2026DiffSDA: Unsupervised Diffusion Sequential Disentanglement Across Modalities
54. ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
55. ICLR 2026Disentangled representation learning through unsupervised symmetry group discovery
56. ICLR 2026Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation
57. ICLR 2026DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick
58. ICLR 2026Diverse Dictionary Learning
59. ICLR 2026Don't Forget Its Variance! The Minimum Path Variance Principle for Accurate and Stable Score-Based Models
60. ICLR 2026Dual Perspectives on Non-Contrastive Self-Supervised Learning
61. ICLR 2026Dual-Branch Representations with Dynamic Gated Fusion and Triple-Granularity Alignment for Deep Multi-View Clustering
62. ICLR 2026Einstein Fields: A Neural Perspective To Computational General Relativity
63. ICLR 2026Error Feedback for Muon and Friends
64. ICLR 2026Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
65. ICLR 2026Explainable $ K $-means Neural Networks for Multi-view Clustering
66. ICLR 2026Fairness via Independence: A General Regularization Framework for Machine Learning
67. ICLR 2026FeDaL: Federated Dataset Learning for General Time Series Foundation Models
68. ICLR 2026Federated Graph-Level Clustering Network with Dual Knowledge Separation
69. ICLR 2026FedOpenMatch: Towards Semi-Supervised Federated Learning in Open-Set Environments
70. ICLR 2026Fine-Grained Class-Conditional Distribution Balancing for Debiased Learning
71. ICLR 2026FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
72. ICLR 2026Fore-Mamba3D: Mamba-based Foreground-Enhanced Encoding for 3D Object Detection
73. ICLR 2026From Parameters to Behaviors: Unsupervised Compression of the Policy Space
74. ICLR 2026From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
75. ICLR 2026From Vicious to Virtuous Cycles: Synergistic Representation Learning for Unsupervised Video Object-Centric Learning
76. ICLR 2026FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing
77. ICLR 2026Gauge Flow Matching: Efficient Constrained Generative Modeling over General Convex Set and Beyond
78. ICLR 2026General Exploratory Bonus for Optimistic Exploration in RLHF
79. ICLR 2026General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess
80. ICLR 2026Generalization Below the Edge of Stability: The Role of Data Geometry
81. ICLR 2026Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss
82. ICLR 2026GmNet: Revisiting Gating Mechanisms From A Frequency View
83. ICLR 2026Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region
84. ICLR 2026GTM: A General Time-series Model for Enhanced Representation Learning of Time-Series data
85. ICLR 2026Hidden Breakthroughs in Language Model Training
86. ICLR 2026Hierarchical Encoding Tree with Modality Mixup for Cross-modal Hashing
87. ICLR 2026How Far Can Unsupervised RLVR Scale LLM Training?
88. ICLR 2026Identifiability and recoverability in self-supervised models
89. ICLR 2026Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment
90. ICLR 2026Improving Set Function Approximation with Quasi-Arithmetic Neural Networks
91. ICLR 2026In Context Semi-Supervised Learning
92. ICLR 2026Incomplete Multi-View Multi-Label Classification via Shared Codebook and Fused-Teacher Self-Distillation
93. ICLR 2026InfoNCE Induces Gaussian Distribution
94. ICLR 2026Internal Evaluation of Density-Based Clusterings with Noise
95. ICLR 2026InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models
96. ICLR 2026Jacobian Aligned Random Forests
97. ICLR 2026KDP: Simplifying Representation Dynamics in Kernel Space
98. ICLR 2026KLAS: Using Similarity to Stitch Neural Networks for an Improved Accuracy-Efficiency Tradeoff
99. ICLR 2026Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
100. ICLR 2026Large Language Model Compression with Global Rank and Sparsity Optimization

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。