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 2,682 篇，第 10 / 54 页

451. ICML 2026MoCL: Metabolic Optimization for Curvature-Aware Continual Learning
452. ICML 2026Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
453. ICML 2026Multi-View Causal Discovery without Non-Gaussianity: Identifiability and Algorithms
454. ICML 2026Multimodal Nested Learning for Decoupled and Coordinated Optimization
455. ICML 2026Multivariate Distributional Reinforcement Learning Using Sliced Divergences
456. ICML 2026Multiview Self-Representation Learning across Heterogeneous Views
457. ICML 2026nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
458. ICML 2026Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
459. ICML 2026Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains
460. ICML 2026NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
461. ICML 2026New Algorithms for Fully-Dynamic k-center with Outliers
462. ICML 2026Newton-coupled Dual-Teacher Semi-supervised Learning Framework
463. ICML 2026Noise-Robust Density Estimation for Tabular Data Anomaly Detection
464. ICML 2026Nonlinear Covariate Balance in Experimental Design
465. ICML 2026Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
466. ICML 2026Omitted Variable Bias in Language Models Under Distribution Shift
467. ICML 2026On Contraction of Sequential and Offset Rademacher Complexities
468. ICML 2026On Learnability and Disambiguation of Multiclass Partial Concept Classes
469. ICML 2026On Testing Conditional Mean Independence for Manifold-Valued Data
470. ICML 2026On the Difficulty of Learning a Meta-network for Training Data Selection
471. ICML 2026On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach
472. ICML 2026On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
473. ICML 2026On the Plasticity and Stability for Post-Training Large Language Models
474. ICML 2026On the Power of Statistics in Class-Incremental Learning with Pretrained Models
475. ICML 2026One Batch Is Enough: A Unified Dataset Condensation Framework for General Time Series Analysis
476. ICML 2026One Coin Has Two Sides: Single Poistive Multi Label Learning from Salient Annotations
477. ICML 2026One-shot Conditional Sampling: MMD meets Nearest Neighbors
478. ICML 2026Online Learning and Inference for Cox Proportional Hazards Model Using Renewable Sieve Estimation
479. ICML 2026OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
480. ICML 2026Optimal Learning from Label Proportions with General Loss Functions
481. ICML 2026Optimal structure learning and conditional independence testing
482. ICML 2026Optimal Top-$k$ Identification from Pairwise Comparisons
483. ICML 2026Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
484. ICML 2026OPTION: Optimal Transport–Guided Flow Matching for Incomplete and Unaligned Multi-View Clustering
485. ICML 2026Orthogonal Model Merging
486. ICML 2026OvisOCR: End-to-End Document Parsing via Aligning Specialized Perception with General Reasoning
487. ICML 2026PACE: Parameter Change for Unsupervised Environment Design
488. ICML 2026PartCo: Part-Level Correspondence Priors Enhance Category Discovery
489. ICML 2026Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
490. ICML 2026Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport
491. ICML 2026PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
492. ICML 2026Positive-Unlabeled Learning with Extreme Scarcity of Labeled Positives
493. ICML 2026PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
494. ICML 2026Powerful and Theoretically Guaranteed Independence Testing on Heterogeneous Federated Clients
495. ICML 2026Predictive variational inference: Learn the predictively optimal posterior distribution
496. ICML 2026Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
497. ICML 2026PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning
498. ICML 2026Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis
499. ICML 2026Quantifying Frontier LLM Capabilities for Container Sandbox Escape
500. ICML 2026Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised 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。