General ML · unsupervised and semisupervised learning papers, 2023–2026

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.

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

2,682 papers, page 45 of 54

2201. ICLR 2023Unsupervised Learning for Combinatorial Optimization Needs Meta Learning
2202. ICLR 2023Unsupervised Manifold Alignment with Joint Multidimensional Scaling
2203. ICLR 2023Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
2204. ICLR 2023Unsupervised Model Selection for Time Series Anomaly Detection
2205. ICLR 2023Unsupervised visualization of image datasets using contrastive learning
2206. ICLR 2023Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top
2207. ICLR 2023Variance-Aware Sparse Linear Bandits
2208. ICML 2023A General Representation Learning Framework with Generalization Performance Guarantees
2209. ICML 2023A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
2210. ICML 2023A Mathematical Model for Curriculum Learning for Parities
2211. ICML 2023A Model-Based Method for Minimizing CVaR and Beyond
2212. ICML 2023A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
2213. ICML 2023Adaptive Annealed Importance Sampling with Constant Rate Progress
2214. ICML 2023Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions
2215. ICML 2023Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
2216. ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
2217. ICML 2023Anchor Sampling for Federated Learning with Partial Client Participation
2218. ICML 2023Are Equivariant Equilibrium Approximators Beneficial?
2219. ICML 2023Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations
2220. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
2221. ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
2222. ICML 2023AutoCoreset: An Automatic Practical Coreset Construction Framework
2223. ICML 2023Behavior Contrastive Learning for Unsupervised Skill Discovery
2224. ICML 2023Beyond the Edge of Stability via Two-step Gradient Updates
2225. ICML 2023BiBench: Benchmarking and Analyzing Network Binarization
2226. ICML 2023Calibrating Multimodal Learning
2227. ICML 2023Can Neural Network Memorization Be Localized?
2228. ICML 2023Cell-Free Latent Go-Explore
2229. ICML 2023Certifying Ensembles: A General Certification Theory with S-Lipschitzness
2230. ICML 2023CLUTR: Curriculum Learning via Unsupervised Task Representation Learning
2231. ICML 2023Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis
2232. ICML 2023CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
2233. ICML 2023Combinatorial Neural Bandits
2234. ICML 2023ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
2235. ICML 2023Conditions and Assumptions for Constraint-based Causal Structure Learning
2236. ICML 2023Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation
2237. ICML 2023Continual Learners are Incremental Model Generalizers
2238. ICML 2023Contrastive Learning Meets Homophily: Two Birds with One Stone
2239. ICML 2023Controllability-Aware Unsupervised Skill Discovery
2240. ICML 2023Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
2241. ICML 2023Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
2242. ICML 2023Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum
2243. ICML 2023Deterministic equivalent and error universality of deep random features learning
2244. ICML 2023Differentiable and Transportable Structure Learning
2245. ICML 2023Dimensionality Reduction for General KDE Mode Finding
2246. ICML 2023Discovering Object-Centric Generalized Value Functions From Pixels
2247. ICML 2023Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark
2248. ICML 2023DUET: 2D Structured and Approximately Equivariant Representations
2249. ICML 2023Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
2250. ICML 2023E$(n)$ Equivariant Message Passing Simplicial Networks

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.