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 553 篇，第 4 / 12 页

151. ICLR 2024Ensemble Distillation for Unsupervised Constituency Parsing
152. ICLR 2024Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning
153. ICLR 2024Exploring Diffusion Time-steps for Unsupervised Representation Learning
154. ICLR 2024Exploring the Promise and Limits of Real-Time Recurrent Learning
155. ICLR 2024Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
156. ICLR 2024Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
157. ICLR 2024Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
158. ICLR 2024Faster Approximation of Probabilistic and Distributional Values via Least Squares
159. ICLR 2024Federated Wasserstein Distance
160. ICLR 2024FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
161. ICLR 2024FedImpro: Measuring and Improving Client Update in Federated Learning
162. ICLR 2024FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
163. ICLR 2024Finite Scalar Quantization: VQ-VAE Made Simple
164. ICLR 2024Flow Matching on General Geometries
165. ICLR 2024From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction
166. ICLR 2024G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
167. ICLR 2024GAIA: a benchmark for General AI Assistants
168. ICLR 2024General Graph Random Features
169. ICLR 2024General Stability Analysis for Zeroth-Order Optimization Algorithms
170. ICLR 2024Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
171. ICLR 2024Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks
172. ICLR 2024Ghost on the Shell: An Expressive Representation of General 3D Shapes
173. ICLR 2024Grokking as a First Order Phase Transition in Two Layer Networks
174. ICLR 2024Grounded Object-Centric Learning
175. ICLR 2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram
176. ICLR 2024How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations
177. ICLR 2024How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
178. ICLR 2024Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
179. ICLR 2024Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
180. ICLR 2024Hypergraph Dynamic System
181. ICLR 2024HYPO: Hyperspherical Out-Of-Distribution Generalization
182. ICLR 2024Identifiable Latent Polynomial Causal Models through the Lens of Change
183. ICLR 2024iGraphMix: Input Graph Mixup Method for Node Classification
184. ICLR 2024Image Background Serves as Good Proxy for Out-of-distribution Data
185. ICLR 2024Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models
186. ICLR 2024Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling
187. ICLR 2024InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
188. ICLR 2024InfoCon: Concept Discovery with Generative and Discriminative Informativeness
189. ICLR 2024Inherently Interpretable Time Series Classification via Multiple Instance Learning
190. ICLR 2024Investigating the Benefits of Projection Head for Representation Learning
191. ICLR 2024Is attention required for ICL? Exploring the Relationship Between Model Architecture and In-Context Learning Ability
192. ICLR 2024Jointly-Learned Exit and Inference for a Dynamic Neural Network
193. ICLR 2024Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
194. ICLR 2024Large Language Models as Analogical Reasoners
195. ICLR 2024Large Language Models as Optimizers
196. ICLR 2024Large Language Models as Tool Makers
197. ICLR 2024Layer-wise linear mode connectivity
198. ICLR 2024LCOT: Linear Circular Optimal Transport
199. ICLR 2024LDReg: Local Dimensionality Regularized Self-Supervised Learning
200. ICLR 2024Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation

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。