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 833 篇,第 1 / 17 页
- NeurIPS 2026$f$-GRPO & Beyond: Divergence-Based Reinforcement Learning Algorithms for General LLM Alignment
- NeurIPS 2026A General Concept-based Decomposition for Vision–Language Embeddings
- NeurIPS 2026A general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
- NeurIPS 2026A mathematical theory of balancing relational generalization and memorization
- NeurIPS 2026Algorithms for Linear Equations with Min and Max Operators Under (Absolutely) Halting Condition
- NeurIPS 2026An Analytical Model of Compute-limited Multistage Training Pipelines
- NeurIPS 2026Anchor PCA
- NeurIPS 2026Approximation in Contrastive Representation Learning
- NeurIPS 2026Asymmetric Generalization in Deep CTR Models: A Block-wise Diagnosis
- NeurIPS 2026Attention-based PCA
- NeurIPS 2026Attention-Based Pretraining for Unsupervised Amortized Causal Discovery
- NeurIPS 2026Batched Stochastic Linear Bandits with 1-Bit Communication Constraints
- NeurIPS 2026BDC-Merge: Cross-Architecture Model Merging via Dependency Alignment
- NeurIPS 2026Bellman Contraction under MMD: A Unified Framework
- NeurIPS 2026Beyond ICA: Identifiability by Symmetry Breaking
- NeurIPS 2026Beyond IID: How General Are Tabular Foundation Models, Really?
- NeurIPS 2026Beyond Imputation: Mask-Adaptive Conformal Prediction via Tree Embeddings on General Missing Data Mechanisms
- NeurIPS 2026Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
- NeurIPS 2026Beyond the Training Distribution: Evaluating Predictions Under Distribution Shift and Selection Bias
- NeurIPS 2026Beyond Unidirectional: Unsupervised Trajectory Learning for Omnidirectional Controllable Underwater Image Enhancement
- NeurIPS 2026Blocked Gibbs meets Diffusion Transformers: Unsupervised Learning for Constraint Optimization
- NeurIPS 2026Building Transformation Layers for Riemannian Neural Networks
- NeurIPS 2026Causal Inference for Sequential Settings under Interference and Latent Confounding
- NeurIPS 2026CHORD: Cross-Model Hallucination Detection via Relational Graph Discrimination
- NeurIPS 2026Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples
- NeurIPS 2026Claude Coke: Prevent Automated Crime by Agents
- NeurIPS 2026Closed-Form Implicit Neural Representations
- NeurIPS 2026Codebook-Guided Cross-Modal Knowledge Distillation for Structurally Heterogeneous Features
- NeurIPS 2026Computing Thiele Rules on Interval Elections and their Generalizations
- NeurIPS 2026Contrastive Nonmyopic Objective Cost-Tradeoff Acquisition for Longitudinal Data
- NeurIPS 2026Conveyance: A Versatile Framework for Learning in Structured Class Spaces
- NeurIPS 2026Cross-Architecture Transferability is Width-Confounded:Diagnosis and Subspace Correction
- NeurIPS 2026CTM-AI: A Blueprint for General AI Inspired by a Model of Consciousness
- NeurIPS 2026D-GAP: Improving Out-of-Domain Robustness via Dataset-Agnostic and Gradient-Guided Augmentation in Amplitude and Pixel Spaces
- NeurIPS 2026Data-Driven Covariate Selection for Nonparametric and Cycle-Agnostic Causal Effect Estimation
- NeurIPS 2026Deadline-Constrained Dynamic Workflow Scheduling Can be Cast as a Representation Learning Problem
- NeurIPS 2026Decoupling Label Shift and Surrogate Gradient Errors for Robust Federated Spiking Neural Networks
- NeurIPS 2026Deep Barycentric Regression for Optimal Transport Map Estimation and its Statistical Optimality
- NeurIPS 2026Deep Reasoning in General Purpose Agents via Structured Meta-Cognition
- NeurIPS 2026Density-Ratio Losses for Post-Hoc Learning to Defer
- NeurIPS 2026Distilling Multi-Teacher Scoring Principles for Unsupervised Time Series Anomaly Detection
- NeurIPS 2026Distributional Estimation of 3D Object Orientation
- NeurIPS 2026Do Sparse Autoencoders Learn Meaningful Concept Hierarchies?
- NeurIPS 2026Drifting Fields are not Conservative
- NeurIPS 2026DUIL: Deep Unsupervised Inverse Learning for in situ Macromolecular Morphology Identification
- NeurIPS 2026Efficient Transferable Optimal Transport via Min-Sliced Transport Plans
- NeurIPS 2026Evaluating Test-Time Scaling of General LLM Agents
- NeurIPS 2026Fast Approximate $\ell_p$ Chamfer Distance via Lopsided Embeddings and Structured JL
- NeurIPS 2026Finding Koopman Invariant Subspaces via Personalized PageRank
- NeurIPS 2026Fisher information and the geometry of memorization in neural networks
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。