通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026
通用机器学习:unsupervised_and_semisupervised_learning
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 2,683 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
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 239 篇,第 1 / 5 页
- ICML 2025A Certified Unlearning Approach without Access to Source Data
- ICML 2025A General Framework for Inference-time Scaling and Steering of Diffusion Models
- ICML 2025A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition
- ICML 2025A General Representation-Based Approach to Multi-Source Domain Adaptation
- ICML 2025A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings
- ICML 2025A Sample Efficient Conditional Independence Test in the Presence of Discretization
- ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
- ICML 2025A Theoretical Framework For Overfitting In Energy-based Modeling
- ICML 2025ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence
- ICML 2025Active feature acquisition via explainability-driven ranking
- ICML 2025Active Treatment Effect Estimation via Limited Samples
- ICML 2025Adaptive Estimation and Learning under Temporal Distribution Shift
- ICML 2025Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
- ICML 2025Adversarial Combinatorial Semi-bandits with Graph Feedback
- ICML 2025Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
- ICML 2025Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
- ICML 2025An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective
- ICML 2025An Expressive and Self-Adaptive Dynamical System for Efficient Function Learning
- ICML 2025Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
- ICML 2025Approximately Correct Label Distribution Learning
- ICML 2025ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
- ICML 2025AutoAL: Automated Active Learning with Differentiable Query Strategy Search
- ICML 2025Autoencoder-Based Hybrid Replay for Class-Incremental Learning
- ICML 2025Automatic Reward Shaping from Confounded Offline Data
- ICML 2025Automatically Identify and Rectify: Robust Deep Contrastive Multi-view Clustering in Noisy Scenarios
- ICML 2025Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
- ICML 2025Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data
- ICML 2025Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
- ICML 2025Banyan: Improved Representation Learning with Explicit Structure
- ICML 2025BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation
- ICML 2025Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments
- ICML 2025BECAME: Bayesian Continual Learning with Adaptive Model Merging
- ICML 2025Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
- ICML 2025Best Subset Selection: Optimal Pursuit for Feature Selection and Elimination
- ICML 2025Beyond Self-Repellent Kernels: History-Driven Target Towards Efficient Nonlinear MCMC on General Graphs
- ICML 2025Bivariate Causal Discovery with Proxy Variables: Integral Solving and Beyond
- ICML 2025Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO*
- ICML 2025Bridging Fairness and Efficiency in Conformal Inference: A Surrogate-Assisted Group-Clustered Approach
- ICML 2025BSLoRA: Enhancing the Parameter Efficiency of LoRA with Intra-Layer and Inter-Layer Sharing
- ICML 2025CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
- ICML 2025CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation
- ICML 2025CALM: Consensus-Aware Localized Merging for Multi-Task Learning
- ICML 2025Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
- ICML 2025Competing Bandits in Matching Markets via Super Stability
- ICML 2025Compute or Load KV Cache? Why Not Both?
- ICML 2025Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows
- ICML 2025Concentration Distribution Learning from Label Distributions
- ICML 2025Concept-Based Unsupervised Domain Adaptation
- ICML 2025Confidence Difference Reflects Various Supervised Signals in Confidence-Difference Classification
- ICML 2025Conformal Anomaly Detection in Event Sequences
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查通用机器学习 · unsupervised and semisupervised learning在 ICML 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "gml-unsupervised-and-semisupervised-learning"}
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。