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 8 / 12 页

351. ICML 2024Disentanglement Learning via Topology
352. ICML 2024Do Efficient Transformers Really Save Computation?
353. ICML 2024Double Stochasticity Gazes Faster: Snap-Shot Decentralized Stochastic Gradient Tracking Methods
354. ICML 2024Dynamic Facility Location in High Dimensional Euclidean Spaces
355. ICML 2024EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
356. ICML 2024Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
357. ICML 2024Estimating Barycenters of Distributions with Neural Optimal Transport
358. ICML 2024Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
359. ICML 2024Faster Sampling via Stochastic Gradient Proximal Sampler
360. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
361. ICML 2024Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
362. ICML 2024Generalization Analysis of Stochastic Weight Averaging with General Sampling
363. ICML 2024GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
364. ICML 2024GNNs Also Deserve Editing, and They Need It More Than Once
365. ICML 2024How Flawed Is ECE? An Analysis via Logit Smoothing
366. ICML 2024Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
367. ICML 2024IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
368. ICML 2024Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy
369. ICML 2024Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
370. ICML 2024Improving Diffusion Models for Inverse Problems Using Optimal Posterior Covariance
371. ICML 2024Improving Neural Logic Machines via Failure Reflection
372. ICML 2024IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation
373. ICML 2024Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping
374. ICML 2024Learning to Explore in POMDPs with Informational Rewards
375. ICML 2024Let Go of Your Labels with Unsupervised Transfer
376. ICML 2024Leveraging VLM-Based Pipelines to Annotate 3D Objects
377. ICML 2024LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
378. ICML 2024Localizing Task Information for Improved Model Merging and Compression
379. ICML 2024LPGD: A General Framework for Backpropagation through Embedded Optimization Layers
380. ICML 2024Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
381. ICML 2024No-Regret Reinforcement Learning in Smooth MDPs
382. ICML 2024On Interpolating Experts and Multi-Armed Bandits
383. ICML 2024On the Consistency of Kernel Methods with Dependent Observations
384. ICML 2024On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
385. ICML 2024Online Algorithms with Uncertainty-Quantified Predictions
386. ICML 2024Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
387. ICML 2024Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research
388. ICML 2024Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
389. ICML 2024Post-hoc Part-Prototype Networks
390. ICML 2024Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms
391. ICML 2024Provable Interactive Learning with Hindsight Instruction Feedback
392. ICML 2024Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation
393. ICML 2024Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
394. ICML 2024Refining Minimax Regret for Unsupervised Environment Design
395. ICML 2024Reinforcement Learning and Regret Bounds for Admission Control
396. ICML 2024ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models
397. ICML 2024Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas
398. ICML 2024Risk Estimation in a Markov Cost Process: Lower and Upper Bounds
399. ICML 2024Roping in Uncertainty: Robustness and Regularization in Markov Games
400. ICML 2024Second-Order Uncertainty Quantification: A Distance-Based Approach

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。