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 318 篇，第 2 / 7 页

51. NeurIPS 2023Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
52. NeurIPS 2023Causal Fairness for Outcome Control
53. NeurIPS 2023Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
54. NeurIPS 2023CEIL: Generalized Contextual Imitation Learning
55. NeurIPS 2023Certification of Distributional Individual Fairness
56. NeurIPS 2023Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
57. NeurIPS 2023Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark
58. NeurIPS 2023ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
59. NeurIPS 2023ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
60. NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
61. NeurIPS 2023Clustering the Sketch: Dynamic Compression for Embedding Tables
62. NeurIPS 2023CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation
63. NeurIPS 2023CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra
64. NeurIPS 2023Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
65. NeurIPS 2023Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
66. NeurIPS 2023Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
67. NeurIPS 2023Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy
68. NeurIPS 2023Consensus and Subjectivity of Skin Tone Annotation for ML Fairness
69. NeurIPS 2023Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities
70. NeurIPS 2023Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time
71. NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
72. NeurIPS 2023Convolutional Neural Operators for robust and accurate learning of PDEs
73. NeurIPS 2023Corruption-Robust Offline Reinforcement Learning with General Function Approximation
74. NeurIPS 2023Creating a Public Repository for Joining Private Data
75. NeurIPS 2023CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation
76. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
77. NeurIPS 2023D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
78. NeurIPS 2023Data-Informed Geometric Space Selection
79. NeurIPS 2023Debiased and Denoised Entity Recognition from Distant Supervision
80. NeurIPS 2023Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
81. NeurIPS 2023Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
82. NeurIPS 2023Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
83. NeurIPS 2023Delegated Classification
84. NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
85. NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
86. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
87. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
88. NeurIPS 2023Disentanglement via Latent Quantization
89. NeurIPS 2023Disentangling Voice and Content with Self-Supervision for Speaker Recognition
90. NeurIPS 2023Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning
91. NeurIPS 2023Distribution Learnability and Robustness
92. NeurIPS 2023Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
93. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
94. NeurIPS 2023Dynamic Non-monotone Submodular Maximization
95. NeurIPS 2023Dynamic Pricing and Learning with Bayesian Persuasion
96. NeurIPS 2023Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
97. NeurIPS 2023Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
98. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
99. NeurIPS 2023Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
100. NeurIPS 2023Equal Opportunity of Coverage in Fair Regression

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。