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 553 篇，第 9 / 12 页
- ICML 2024Sequential Disentanglement by Extracting Static Information From A Single Sequence Element
- ICML 2024Simplicity Bias of Two-Layer Networks beyond Linearly Separable Data
- ICML 2024Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks
- ICML 2024SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms
- ICML 2024Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features
- ICML 2024Stochastic Quantum Sampling for Non-Logconcave Distributions and Estimating Partition Functions
- ICML 2024Studying K-FAC Heuristics by Viewing Adam through a Second-Order Lens
- ICML 2024Switched Flow Matching: Eliminating Singularities via Switching ODEs
- ICML 2024Switching the Loss Reduces the Cost in Batch Reinforcement Learning
- ICML 2024Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
- ICML 2024Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
- ICML 2024Tell, Don't Show: Language Guidance Eases Transfer Across Domains in Images and Videos
- ICML 2024The Balanced-Pairwise-Affinities Feature Transform
- ICML 2024The Computational Complexity of Finding Second-Order Stationary Points
- ICML 2024The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
- ICML 2024The WMDP Benchmark: Measuring and Reducing Malicious Use with Unlearning
- ICML 2024Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
- ICML 2024Towards General Neural Surrogate Solvers with Specialized Neural Accelerators
- ICML 2024Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
- ICML 2024Transolver: A Fast Transformer Solver for PDEs on General Geometries
- ICML 2024Transport of Algebraic Structure to Latent Embeddings
- ICML 2024UGrid: An Efficient-And-Rigorous Neural Multigrid Solver for Linear PDEs
- ICML 2024Uncertainty-Aware Reward-Free Exploration with General Function Approximation
- ICML 2024Understanding MLP-Mixer as a wide and sparse MLP
- ICML 2024Universal Consistency of Wide and Deep ReLU Neural Networks and Minimax Optimal Convergence Rates for Kolmogorov-Donoho Optimal Function Classes
- ICML 2024Unsupervised Concept Discovery Mitigates Spurious Correlations
- ICML 2024Unsupervised Domain Adaptation for Anatomical Structure Detection in Ultrasound Images
- ICML 2024Unsupervised Evaluation of Code LLMs with Round-Trip Correctness
- ICML 2024Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms
- ICML 2024Unsupervised Representation Learning of Brain Activity via Bridging Voxel Activity and Functional Connectivity
- ICML 2024Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
- ICML 2024UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
- ICML 2024What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
- ICML 2024WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer
- ICML 2024Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion
- NeurIPS 2024A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
- NeurIPS 2024Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
- NeurIPS 2024Active Learning of General Halfspaces: Label Queries vs Membership Queries
- NeurIPS 2024Adaptive Exploration for Data-Efficient General Value Function Evaluations
- NeurIPS 2024Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
- NeurIPS 2024Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem
- NeurIPS 2024Approximately Equivariant Neural Processes
- NeurIPS 2024ARC: A Generalist Graph Anomaly Detector with In-Context Learning
- NeurIPS 2024Are Graph Neural Networks Optimal Approximation Algorithms?
- NeurIPS 2024Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis
- NeurIPS 2024Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning
- NeurIPS 2024CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
- NeurIPS 2024Compositional PAC-Bayes: Generalization of GNNs with persistence and beyond
- NeurIPS 2024Contextual Multinomial Logit Bandits with General Value Functions
- NeurIPS 2024Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification
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。