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 833 篇，第 13 / 17 页

601. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
602. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
603. NeurIPS 2023Disentanglement via Latent Quantization
604. NeurIPS 2023Disentangling Voice and Content with Self-Supervision for Speaker Recognition
605. NeurIPS 2023Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning
606. NeurIPS 2023Distribution Learnability and Robustness
607. NeurIPS 2023Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
608. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
609. NeurIPS 2023Dynamic Non-monotone Submodular Maximization
610. NeurIPS 2023Dynamic Pricing and Learning with Bayesian Persuasion
611. NeurIPS 2023Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
612. NeurIPS 2023Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
613. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
614. NeurIPS 2023Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
615. NeurIPS 2023Equal Opportunity of Coverage in Fair Regression
616. NeurIPS 2023Equivariant Single View Pose Prediction Via Induced and Restriction Representations
617. NeurIPS 2023Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors
618. NeurIPS 2023Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
619. NeurIPS 2023Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
620. NeurIPS 2023Explain Any Concept: Segment Anything Meets Concept-Based Explanation
621. NeurIPS 2023Explaining Predictive Uncertainty with Information Theoretic Shapley Values
622. NeurIPS 2023f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences
623. NeurIPS 2023FABind: Fast and Accurate Protein-Ligand Binding
624. NeurIPS 2023Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network
625. NeurIPS 2023Fair Allocation of Indivisible Chores: Beyond Additive Costs
626. NeurIPS 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
627. NeurIPS 2023Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
628. NeurIPS 2023Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
629. NeurIPS 2023Fed-CO$_{2}$: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
630. NeurIPS 2023Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
631. NeurIPS 2023Federated Learning with Manifold Regularization and Normalized Update Reaggregation
632. NeurIPS 2023Federated Spectral Clustering via Secure Similarity Reconstruction
633. NeurIPS 2023FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
634. NeurIPS 2023First- and Second-Order Bounds for Adversarial Linear Contextual Bandits
635. NeurIPS 2023Fundamental Limits and Tradeoffs in Invariant Representation Learning
636. NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
637. NeurIPS 2023Generalized equivalences between subsampling and ridge regularization
638. NeurIPS 2023GLIME: General, Stable and Local LIME Explanation
639. NeurIPS 2023Globally injective and bijective neural operators
640. NeurIPS 2023Granger Components Analysis: Unsupervised learning of latent temporal dependencies
641. NeurIPS 2023Graph Contrastive Learning with Stable and Scalable Spectral Encoding
642. NeurIPS 2023Graph Convolutional Kernel Machine versus Graph Convolutional Networks
643. NeurIPS 2023GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
644. NeurIPS 2023H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
645. NeurIPS 2023H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training
646. NeurIPS 2023Harnessing the power of choices in decision tree learning
647. NeurIPS 2023Have it your way: Individualized Privacy Assignment for DP-SGD
648. NeurIPS 2023Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection
649. NeurIPS 2023How a Student becomes a Teacher: learning and forgetting through Spectral methods
650. NeurIPS 2023How many samples are needed to leverage smoothness?

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。