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 859 篇，第 2 / 18 页

51. ICML 2026Causal discovery for time series with endogenous context variables
52. ICML 2026Causal Identification from Counterfactual Data: Completeness and Bounding Results
53. ICML 2026Causal Representation Learning with Optimal Compression and Complex Treatments
54. ICML 2026CausalProfiler: Generating Synthetic Benchmarks for Rigorous and Transparent Evaluation of Causal Machine Learning
55. ICML 2026CE$^4$L: Continual Ego, Exo, and Ego-Exo Learning
56. ICML 2026CHB: A Diagnostic Toolkit for Hardness-Aware Clustering Evaluation
57. ICML 2026CL-GCL: Comprehensive and Lightweight Graph Contrastive Learning
58. ICML 2026CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
59. ICML 2026CLASP: Online learning algorithms for Convex Losses And Squared Penalties
60. ICML 2026Class-Grouped Normalized Momentum and Faster Hyperparameter Exploration to Tackle Class Imbalance in Federated Learning
61. ICML 2026Class-Prior Perturbation-Robust Regularization for Imbalanced Unreliable Partial Label Learning
62. ICML 2026CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
63. ICML 2026Clustered Influence Functions
64. ICML 2026CoCoQuant: Breaking the Bandwidth Wall via Co-Optimized Communication and Computation Quantization
65. ICML 2026CodeClash: Benchmarking Goal-Oriented Software Engineering
66. ICML 2026COGNOS: Universal Enhancement for Time Series Anomaly Detection via Constrained Gaussian-Noise Optimization and Smoothing
67. ICML 2026Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
68. ICML 2026Component-Wise Composite Likelihood Distillation for Censored Time-to-Event Data
69. ICML 2026Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
70. ICML 2026Conditional Quantile Adjusted Conformal Prediction for Time Series
71. ICML 2026Conf-Gen: Conformal Uncertainty Quantification for Generative Models
72. ICML 2026Conformal Reliability: A New Evaluation Metric for Conditional Generation
73. ICML 2026CONGA:Confidence-and-Gradient-Aware Learning Rate Schedule for Test Time Adaptation
74. ICML 2026Continual Learning of Domain-Invariant Representations
75. ICML 2026CONTINUUM: Restoring the Contiguous Tensor Abstraction Efficiently for Dynamic AI Workloads via Hardware Virtualization
76. ICML 2026Contrastive Order Learning: A General Framework for Ordinal Regression
77. ICML 2026Contrastive Symbolic Regression: Aligned Representations, Adaptive Prediction, and Diverse Ensembles
78. ICML 2026Convergence of Steepest Descent and Adam under Non-Uniform Smoothness
79. ICML 2026Correcting Split Selection in Online Decision Trees via Anytime-Valid Inference
80. ICML 2026Coupled Trigger Optimization and Vulnerable Parameter Alignment for Persistent Backdoor Attacks on Federated Learning
81. ICML 2026Cross-Modal Knowledge Distillation without Paired Data: Theoretical Foundation and Algorithm
82. ICML 2026Cross-View Lewis Weight Fusion Empowering Exemplar Replay for Federated Class-Incremental Learning
83. ICML 2026cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
84. ICML 2026DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables
85. ICML 2026DAL: A Practical Prior-Free Black-Box Framework for Piecewise Stationary Bandits
86. ICML 2026Deep Multi-view Graph Clustering via Attribute-aware Bidirectional Structural Refinement and Pseudo-label Guided Multi-level Fusion
87. ICML 2026Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success
88. ICML 2026Design-Based Anytime-Valid Inference for Randomized Experiments with Delayed Outcomes and Staggered Entry
89. ICML 2026DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning
90. ICML 2026Dimensionality Reduction with Point-distributions Similarity Invariant
91. ICML 2026DISCO: Mitigating Bias in Deep Learning with Conditional Distance Correlation
92. ICML 2026DiScoFormer: Plug-In Density and Score Estimation with Transformers
93. ICML 2026Discretized Density-Guided Source-Free Domain Adaptation for Regression
94. ICML 2026Dissecting Causal Mechanism Shifts via FANS: Function And Noise Separation
95. ICML 2026Distilling Linearized Behavior into Non-linear Fine-Tuning for Effective Task Arithmetic
96. ICML 2026Divisiveness-Consistent Label Distribution Learning
97. ICML 2026DMCO: Budget-Aware Co-Optimization of Data Cleaning and AutoML
98. ICML 2026Do LLMs Signal When They’re Right? Evidence from Neuron Agreement
99. ICML 2026Doc-to-LoRA: Learning to Instantly Internalize Contexts
100. ICML 2026Domain Adaptation with Adaptive $f$-Divergence: Tighter Variational Representation and Generalization Bounds

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。