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

649 papers, page 6 of 13

251. ICML 2023Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
252. ICML 2023Learning Control-Oriented Dynamical Structure from Data
253. ICML 2023Learning Distributions over Quantum Measurement Outcomes
254. ICML 2023Learning Rate Schedules in the Presence of Distribution Shift
255. ICML 2023Learning Representations without Compositional Assumptions
256. ICML 2023Learning to Boost Training by Periodic Nowcasting Near Future Weights
257. ICML 2023Learning to Initiate and Reason in Event-Driven Cascading Processes
258. ICML 2023Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
259. ICML 2023Learning useful representations for shifting tasks and distributions
260. ICML 2023Learning-Rate-Free Learning by D-Adaptation
261. ICML 2023Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data
262. ICML 2023Lower Bounds for Learning in Revealing POMDPs
263. ICML 2023Machine Learning Force Fields with Data Cost Aware Training
264. ICML 2023Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
265. ICML 2023Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming
266. ICML 2023Mixture Proportion Estimation Beyond Irreducibility
267. ICML 2023Model-Aware Contrastive Learning: Towards Escaping the Dilemmas
268. ICML 2023Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
269. ICML 2023Multiply Robust Off-policy Evaluation and Learning under Truncation by Death
270. ICML 2023Near-Optimal $\Phi$-Regret Learning in Extensive-Form Games
271. ICML 2023No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation
272. ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
273. ICML 2023Nonparametric Iterative Machine Teaching
274. ICML 2023NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
275. ICML 2023Offline Learning in Markov Games with General Function Approximation
276. ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
277. ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
278. ICML 2023On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs
279. ICML 2023On the Privacy-Robustness-Utility Trilemma in Distributed Learning
280. ICML 2023Optimal Arms Identification with Knapsacks
281. ICML 2023Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
282. ICML 2023Optimal Sets and Solution Paths of ReLU Networks
283. ICML 2023PaLM-E: An Embodied Multimodal Language Model
284. ICML 2023Parallel Neurosymbolic Integration with Concordia
285. ICML 2023Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach
286. ICML 2023Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
287. ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
288. ICML 2023Principled Acceleration of Iterative Numerical Methods Using Machine Learning
289. ICML 2023Prototype-oriented unsupervised anomaly detection for multivariate time series
290. ICML 2023Provably and Practically Efficient Neural Contextual Bandits
291. ICML 2023Provably Invariant Learning without Domain Information
292. ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
293. ICML 2023Random Teachers are Good Teachers
294. ICML 2023Regret Minimization and Convergence to Equilibria in General-sum Markov Games
295. ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
296. ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
297. ICML 2023Rethinking Backdoor Attacks
298. ICML 2023Rethinking Weak Supervision in Helping Contrastive Learning
299. ICML 2023Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
300. ICML 2023Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees

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.