General ML · unsupervised and semisupervised learning papers, 2023–2026
General machine learning: unsupervised_and_semisupervised_learning
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 2,683 papers are tagged with this topic.
Key findings
- General ML · unsupervised and semisupervised learning went from 649 papers in 2023 to 799 in 2026, roughly 1.2x in three years.
- ICML publishes the most General ML · unsupervised and semisupervised learning work: 859 papers from 2023 to 2026, 32% of the four-venue total.
- The fastest-growing overlap is with Deep learning · self supervised learning: papers tagged with both rose from 23 in 2023 to 86 in 2026.
- Among the 6 topics under General Machine Learning, it ranks #1 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 1.2x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
Representative papers
Spread across years and venues so every edition shows up
- 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
All General ML · unsupervised and semisupervised learning papers
833 papers, page 14 of 17
- NeurIPS 2023How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget
- NeurIPS 2023HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection
- NeurIPS 2023Human-Aligned Calibration for AI-Assisted Decision Making
- NeurIPS 2023ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
- NeurIPS 2023Implicit Regularization in Over-Parameterized Support Vector Machine
- NeurIPS 2023Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
- NeurIPS 2023Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms
- NeurIPS 2023Improved Frequency Estimation Algorithms with and without Predictions
- NeurIPS 2023In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
- NeurIPS 2023Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization
- NeurIPS 2023Incentives in Private Collaborative Machine Learning
- NeurIPS 2023Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
- NeurIPS 2023Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills
- NeurIPS 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
- NeurIPS 2023InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
- NeurIPS 2023Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
- NeurIPS 2023Invariant Learning via Probability of Sufficient and Necessary Causes
- NeurIPS 2023Inverse Reinforcement Learning with the Average Reward Criterion
- NeurIPS 2023Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning
- NeurIPS 2023Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition
- NeurIPS 2023Kernelized Cumulants: Beyond Kernel Mean Embeddings
- NeurIPS 2023KuaiSim: A Comprehensive Simulator for Recommender Systems
- NeurIPS 2023Learning and Collusion in Multi-unit Auctions
- NeurIPS 2023Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
- NeurIPS 2023Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
- NeurIPS 2023Learning Exponential Families from Truncated Samples
- NeurIPS 2023Learning From Biased Soft Labels
- NeurIPS 2023Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
- NeurIPS 2023Learning Motion Refinement for Unsupervised Face Animation
- NeurIPS 2023Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
- NeurIPS 2023Learning to Configure Separators in Branch-and-Cut
- NeurIPS 2023Learning to Discover Skills through Guidance
- NeurIPS 2023Learning Universal Policies via Text-Guided Video Generation
- NeurIPS 2023Leveraging sparse and shared feature activations for disentangled representation learning
- NeurIPS 2023List and Certificate Complexities in Replicable Learning
- NeurIPS 2023Lo-Hi: Practical ML Drug Discovery Benchmark
- NeurIPS 2023Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
- NeurIPS 2023Lovász Principle for Unsupervised Graph Representation Learning
- NeurIPS 2023M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery
- NeurIPS 2023Machine learning detects terminal singularities
- NeurIPS 2023Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
- NeurIPS 2023Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration
- NeurIPS 2023Maximum Average Randomly Sampled: A Scale Free and Non-parametric Algorithm for Stochastic Bandits
- NeurIPS 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
- NeurIPS 2023Metis: Understanding and Enhancing In-Network Regular Expressions
- NeurIPS 2023Minimum Description Length and Generalization Guarantees for Representation Learning
- NeurIPS 2023Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
- NeurIPS 2023MLFMF: Data Sets for Machine Learning for Mathematical Formalization
- NeurIPS 2023MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting
- NeurIPS 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability
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FAQ
- How many General ML · unsupervised and semisupervised learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 2,683 in total: 649 in 2023, 553 in 2024, 682 in 2025, 799 in 2026.
- How many General ML · unsupervised and semisupervised learning papers are at NeurIPS 2026?
- NeurIPS 2026 has 194 General ML · unsupervised and semisupervised learning papers, versus 203 the year before.
- How many General ML · unsupervised and semisupervised learning papers are at ICLR 2026?
- ICLR 2026 has 187 General ML · unsupervised and semisupervised learning papers, versus 174 the year before.
- How many General ML · unsupervised and semisupervised learning papers are at ICML 2026?
- ICML 2026 has 348 General ML · unsupervised and semisupervised learning papers, versus 239 the year before.
- How many General ML · unsupervised and semisupervised learning papers are at CVPR 2026?
- CVPR 2026 has 70 General ML · unsupervised and semisupervised learning papers, versus 66 the year before.
- Which conference publishes the most General ML · unsupervised and semisupervised learning papers?
- ICML, with 859 papers from 2023 to 2026.