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
2,682 papers, page 47 of 54
- ICML 2023Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes
- ICML 2023Multiply Robust Off-policy Evaluation and Learning under Truncation by Death
- ICML 2023Near-Optimal $\Phi$-Regret Learning in Extensive-Form Games
- ICML 2023No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation
- ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
- ICML 2023Nonparametric Iterative Machine Teaching
- ICML 2023NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
- ICML 2023Offline Learning in Markov Games with General Function Approximation
- ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
- ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
- ICML 2023On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs
- ICML 2023On the Privacy-Robustness-Utility Trilemma in Distributed Learning
- ICML 2023Optimal Arms Identification with Knapsacks
- ICML 2023Optimal randomized multilevel Monte Carlo for repeatedly nested expectations
- ICML 2023Optimal Sets and Solution Paths of ReLU Networks
- ICML 2023PaLM-E: An Embodied Multimodal Language Model
- ICML 2023Parallel Neurosymbolic Integration with Concordia
- ICML 2023Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach
- ICML 2023Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
- ICML 2023Predictable MDP Abstraction for Unsupervised Model-Based RL
- ICML 2023Principled Acceleration of Iterative Numerical Methods Using Machine Learning
- ICML 2023Prototype-oriented unsupervised anomaly detection for multivariate time series
- ICML 2023Provably and Practically Efficient Neural Contextual Bandits
- ICML 2023Provably Invariant Learning without Domain Information
- ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
- ICML 2023Random Teachers are Good Teachers
- ICML 2023Regret Minimization and Convergence to Equilibria in General-sum Markov Games
- ICML 2023Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space
- ICML 2023Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL
- ICML 2023Rethinking Backdoor Attacks
- ICML 2023Rethinking Weak Supervision in Helping Contrastive Learning
- ICML 2023Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
- ICML 2023Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees
- ICML 2023Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation
- ICML 2023Reward-Mixing MDPs with Few Latent Contexts are Learnable
- ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch
- ICML 2023Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
- ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
- ICML 2023Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
- ICML 2023Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation
- ICML 2023Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains
- ICML 2023SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance
- ICML 2023Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
- ICML 2023Sharper Bounds for $\ell_p$ Sensitivity Sampling
- ICML 2023SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
- ICML 2023SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series
- ICML 2023Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning
- ICML 2023State and parameter learning with PARIS particle Gibbs
- ICML 2023STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition
- ICML 2023Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems
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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.