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 203 篇,第 4 / 5 页
- NeurIPS 2025Separating the 'what' and 'how' of compositional computation to enable reuse and continual learning
- NeurIPS 2025Shapley-Based Data Valuation for Weighted $k$-Nearest Neighbors
- NeurIPS 2025SHGR: A Generalized Maximal Correlation Coefficient
- NeurIPS 2025SNAP: Low-Latency Test-Time Adaptation with Sparse Updates
- NeurIPS 2025SORTeD Rashomon Sets of Sparse Decision Trees: Anytime Enumeration
- NeurIPS 2025Spatiotemporal Consensus with Scene Prior for Unsupervised Domain Adaptive Person Search
- NeurIPS 2025Spectral Graph Coarsening Using Inner Product Preservation and the Grassmann Manifold
- NeurIPS 2025SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
- NeurIPS 2025SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
- NeurIPS 2025Split conformal classification with unsupervised calibration
- NeurIPS 2025Stability and Oracle Inequalities for Optimal Transport Maps between General Distributions
- NeurIPS 2025Stochastic Forward-Forward Learning through Representational Dimensionality Compression
- NeurIPS 2025Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization
- NeurIPS 2025Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
- NeurIPS 2025Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
- NeurIPS 2025The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models
- NeurIPS 2025Theoretical Insights into In-context Learning with Unlabeled Data
- NeurIPS 2025Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining
- NeurIPS 2025Tightening Regret Lower and Upper Bounds in Restless Rising Bandits
- NeurIPS 2025Token Perturbation Guidance for Diffusion Models
- NeurIPS 2025Towards a General Attention Framework on Gyrovector Spaces for Matrix Manifolds
- NeurIPS 2025Towards a Pairwise Ranking Model with Orderliness and Monotonicity for Label Enhancement
- NeurIPS 2025Towards General Modality Translation with Contrastive and Predictive Latent Diffusion Bridge
- NeurIPS 2025Towards Unsupervised Domain Bridging via Image Degradation in Semantic Segmentation
- NeurIPS 2025Towards Unsupervised Open-Set Graph Domain Adaptation via Dual Reprogramming
- NeurIPS 2025Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN
- NeurIPS 2025TPP-SD: Accelerating Transformer Point Process Sampling with Speculative Decoding
- NeurIPS 2025Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
- NeurIPS 2025Transductive Conformal Inference for Full Ranking
- NeurIPS 2025Tree Ensemble Explainability through the Hoeffding Functional Decomposition and TreeHFD Algorithm
- NeurIPS 2025Tree-Sliced Entropy Partial Transport
- NeurIPS 2025TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception
- NeurIPS 2025Two‑Stage Learning of Stabilizing Neural Controllers via Zubov Sampling and Iterative Domain Expansion
- NeurIPS 2025U-CAN: Unsupervised Point Cloud Denoising with Consistency-Aware Noise2Noise Matching
- NeurIPS 2025UGM2N: An Unsupervised and Generalizable Mesh Movement Network via M-Uniform Loss
- NeurIPS 2025UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
- NeurIPS 2025Ultrametric Cluster Hierarchies: I Want ‘em All!
- NeurIPS 2025Uncertainty Estimation by Flexible Evidential Deep Learning
- NeurIPS 2025Uni-RL: Unifying Online and Offline RL via Implicit Value Regularization
- NeurIPS 2025UniGist: Towards General and Hardware-aligned Sequence-level Long Context Compression
- NeurIPS 2025Universal Sequence Preconditioning
- NeurIPS 2025Unlabeled Data Improves Fine-Grained Image Zero-shot Classification with Multimodal LLMs
- NeurIPS 2025Unsupervised Federated Graph Learning
- NeurIPS 2025Unsupervised Learning for Optimal Transport plan prediction between unbalanced graphs
- NeurIPS 2025Unsupervised Trajectory Optimization for 3D Registration in Serial Section Electron Microscopy using Neural ODEs
- NeurIPS 2025Unveiling Transformer Perception by Exploring Input Manifolds
- NeurIPS 2025Valid Selection among Conformal Sets
- NeurIPS 2025VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion
- NeurIPS 2025Wasserstein Transfer Learning
- NeurIPS 2025Weak-shot Keypoint Estimation via Keyness and Correspondence Transfer
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。