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

318 papers, page 1 of 7

1. NeurIPS 2023(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
2. NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
3. NeurIPS 2023$L_2$-Uniform Stability of Randomized Learning Algorithms: Sharper Generalization Bounds and Confidence Boosting
4. NeurIPS 2023$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
5. NeurIPS 2023$SE(3)$ Equivariant Convolution and Transformer in Ray Space
6. NeurIPS 2023A Combinatorial Algorithm for Approximating the Optimal Transport in the Parallel and MPC Settings
7. NeurIPS 2023A Competitive Algorithm for Agnostic Active Learning
8. NeurIPS 2023A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
9. NeurIPS 2023A Framework for Fast and Stable Representations of Multiparameter Persistent Homology Decompositions
10. NeurIPS 2023A General Framework for Equivariant Neural Networks on Reductive Lie Groups
11. NeurIPS 2023A General Framework for Robust G-Invariance in G-Equivariant Networks
12. NeurIPS 2023A General Theory of Correct, Incorrect, and Extrinsic Equivariance
13. NeurIPS 2023A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
14. NeurIPS 2023A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
15. NeurIPS 2023A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications
16. NeurIPS 2023A Theory of Unsupervised Translation Motivated by Understanding Animal Communication
17. NeurIPS 2023A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning
18. NeurIPS 2023A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process
19. NeurIPS 2023A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm
20. NeurIPS 2023A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning
21. NeurIPS 2023A Unified Model and Dimension for Interactive Estimation
22. NeurIPS 2023A Unified Solution for Privacy and Communication Efficiency in Vertical Federated Learning
23. NeurIPS 2023Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
24. NeurIPS 2023Accessing Higher Dimensions for Unsupervised Word Translation
25. NeurIPS 2023Active representation learning for general task space with applications in robotics
26. NeurIPS 2023Adaptive Linear Estimating Equations
27. NeurIPS 2023Adaptive Topological Feature via Persistent Homology: Filtration Learning for Point Clouds
28. NeurIPS 2023Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
29. NeurIPS 2023Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions
30. NeurIPS 2023Adversarially Robust Learning with Uncertain Perturbation Sets
31. NeurIPS 2023Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
32. NeurIPS 2023An Adaptive Algorithm for Learning with Unknown Distribution Drift
33. NeurIPS 2023Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning
34. NeurIPS 2023Auditing for Human Expertise
35. NeurIPS 2023Balancing memorization and generalization in RNNs for high performance brain-machine Interfaces
36. NeurIPS 2023Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release
37. NeurIPS 2023Batchnorm Allows Unsupervised Radial Attacks
38. NeurIPS 2023Bayesian Learning via Q-Exponential Process
39. NeurIPS 2023Benchmark of Machine Learning Force Fields for Semiconductor Simulations: Datasets, Metrics, and Comparative Analysis
40. NeurIPS 2023Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions
41. NeurIPS 2023Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
42. NeurIPS 2023Beyond Normal: On the Evaluation of Mutual Information Estimators
43. NeurIPS 2023Bicriteria Multidimensional Mechanism Design with Side Information
44. NeurIPS 2023Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
45. NeurIPS 2023Black-Box Differential Privacy for Interactive ML
46. NeurIPS 2023Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
47. NeurIPS 2023Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
48. NeurIPS 2023BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning
49. NeurIPS 2023CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
50. NeurIPS 2023Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents

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.