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 859 篇，第 12 / 18 页

551. ICML 2025The Batch Complexity of Bandit Pure Exploration
552. ICML 2025The Complexity of Learning Sparse Superposed Features with Feedback
553. ICML 2025The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction
554. ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
555. ICML 2025The Relationship Between No-Regret Learning and Online Conformal Prediction
556. ICML 2025Tight and Fast Bounds for Multi-Label Learning
557. ICML 2025Time Series Representations with Hard-Coded Invariances
558. ICML 2025TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
559. ICML 2025To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
560. ICML 2025Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
561. ICML 2025Towards an Explainable Comparison and Alignment of Feature Embeddings
562. ICML 2025Towards Lifelong Model Editing via Simulating Ideal Editor
563. ICML 2025Towards Robustness and Explainability of Automatic Algorithm Selection
564. ICML 2025Towards the Causal Complete Cause of Multi-Modal Representation Learning
565. ICML 2025Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift
566. ICML 2025Towards Understanding Parametric Generalized Category Discovery on Graphs
567. ICML 2025Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
568. ICML 2025UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
569. ICML 2025Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
570. ICML 2025Unified K-Means Clustering with Label-Guided Manifold Learning
571. ICML 2025Universal Neural Optimal Transport
572. ICML 2025unMORE: Unsupervised Multi-Object Segmentation via Center-Boundary Reasoning
573. ICML 2025Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
574. ICML 2025Unsupervised Learning for Class Distribution Mismatch
575. ICML 2025Update Your Transformer to the Latest Release: Re-Basin of Task Vectors
576. ICML 2025Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting
577. ICML 2025Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible
578. ICML 2025Vision-Language Model Selection and Reuse for Downstream Adaptation
579. ICML 2025Volume Optimality in Conformal Prediction with Structured Prediction Sets
580. ICML 2025Volume-Aware Distance for Robust Similarity Learning
581. ICML 2025Wait-Less Offline Tuning and Re-solving for Online Decision Making
582. ICML 2025Weakly Supervised Anomaly Detection via Dual-Tailed Kernel
583. ICML 2025Weakly-Supervised Contrastive Learning for Imprecise Class Labels
584. ICML 2025When Bad Data Leads to Good Models
585. ICML 2025When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
586. ICML 2025Whoever Started the interference Should End It: Guiding Data-Free Model Merging via Task Vectors
587. ICML 2025Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
588. ICML 2024A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
589. ICML 2024A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
590. ICML 2024A General Framework for Learning from Weak Supervision
591. ICML 2024A General Framework for Sequential Decision-Making under Adaptivity Constraints
592. ICML 2024A General Online Algorithm for Optimizing Complex Performance Metrics
593. ICML 2024A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
594. ICML 2024A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
595. ICML 2024A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation
596. ICML 2024A3S: A General Active Clustering Method with Pairwise Constraints
597. ICML 2024Agent Instructs Large Language Models to be General Zero-Shot Reasoners
598. ICML 2024Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms
599. ICML 2024Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms
600. ICML 2024Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses

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。