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 649 篇，第 10 / 13 页

451. NeurIPS 2023Fundamental Limits and Tradeoffs in Invariant Representation Learning
452. NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
453. NeurIPS 2023Generalized equivalences between subsampling and ridge regularization
454. NeurIPS 2023GLIME: General, Stable and Local LIME Explanation
455. NeurIPS 2023Globally injective and bijective neural operators
456. NeurIPS 2023Granger Components Analysis: Unsupervised learning of latent temporal dependencies
457. NeurIPS 2023Graph Contrastive Learning with Stable and Scalable Spectral Encoding
458. NeurIPS 2023Graph Convolutional Kernel Machine versus Graph Convolutional Networks
459. NeurIPS 2023GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
460. NeurIPS 2023H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
461. NeurIPS 2023H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training
462. NeurIPS 2023Harnessing the power of choices in decision tree learning
463. NeurIPS 2023Have it your way: Individualized Privacy Assignment for DP-SGD
464. NeurIPS 2023Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection
465. NeurIPS 2023How a Student becomes a Teacher: learning and forgetting through Spectral methods
466. NeurIPS 2023How many samples are needed to leverage smoothness?
467. NeurIPS 2023How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget
468. NeurIPS 2023HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection
469. NeurIPS 2023Human-Aligned Calibration for AI-Assisted Decision Making
470. NeurIPS 2023ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
471. NeurIPS 2023Implicit Regularization in Over-Parameterized Support Vector Machine
472. NeurIPS 2023Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
473. NeurIPS 2023Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms
474. NeurIPS 2023Improved Frequency Estimation Algorithms with and without Predictions
475. NeurIPS 2023In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
476. NeurIPS 2023Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization
477. NeurIPS 2023Incentives in Private Collaborative Machine Learning
478. NeurIPS 2023Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
479. NeurIPS 2023Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills
480. NeurIPS 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
481. NeurIPS 2023InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
482. NeurIPS 2023Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
483. NeurIPS 2023Invariant Learning via Probability of Sufficient and Necessary Causes
484. NeurIPS 2023Inverse Reinforcement Learning with the Average Reward Criterion
485. NeurIPS 2023Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning
486. NeurIPS 2023Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition
487. NeurIPS 2023Kernelized Cumulants: Beyond Kernel Mean Embeddings
488. NeurIPS 2023KuaiSim: A Comprehensive Simulator for Recommender Systems
489. NeurIPS 2023Learning and Collusion in Multi-unit Auctions
490. NeurIPS 2023Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
491. NeurIPS 2023Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
492. NeurIPS 2023Learning Exponential Families from Truncated Samples
493. NeurIPS 2023Learning From Biased Soft Labels
494. NeurIPS 2023Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
495. NeurIPS 2023Learning Motion Refinement for Unsupervised Face Animation
496. NeurIPS 2023Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
497. NeurIPS 2023Learning to Configure Separators in Branch-and-Cut
498. NeurIPS 2023Learning to Discover Skills through Guidance
499. NeurIPS 2023Learning Universal Policies via Text-Guided Video Generation
500. NeurIPS 2023Leveraging sparse and shared feature activations for disentangled representation 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。