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 12 of 17
- NeurIPS 2023Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release
- NeurIPS 2023Batchnorm Allows Unsupervised Radial Attacks
- NeurIPS 2023Bayesian Learning via Q-Exponential Process
- NeurIPS 2023Benchmark of Machine Learning Force Fields for Semiconductor Simulations: Datasets, Metrics, and Comparative Analysis
- NeurIPS 2023Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions
- NeurIPS 2023Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
- NeurIPS 2023Beyond Normal: On the Evaluation of Mutual Information Estimators
- NeurIPS 2023Bicriteria Multidimensional Mechanism Design with Side Information
- NeurIPS 2023Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
- NeurIPS 2023Black-Box Differential Privacy for Interactive ML
- NeurIPS 2023Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
- NeurIPS 2023Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
- NeurIPS 2023BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning
- NeurIPS 2023CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
- NeurIPS 2023Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
- NeurIPS 2023Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
- NeurIPS 2023Causal Fairness for Outcome Control
- NeurIPS 2023Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
- NeurIPS 2023CEIL: Generalized Contextual Imitation Learning
- NeurIPS 2023Certification of Distributional Individual Fairness
- NeurIPS 2023Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
- NeurIPS 2023Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark
- NeurIPS 2023ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
- NeurIPS 2023ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
- NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
- NeurIPS 2023Clustering the Sketch: Dynamic Compression for Embedding Tables
- NeurIPS 2023CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation
- NeurIPS 2023CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra
- NeurIPS 2023Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
- NeurIPS 2023Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
- NeurIPS 2023Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
- NeurIPS 2023Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy
- NeurIPS 2023Consensus and Subjectivity of Skin Tone Annotation for ML Fairness
- NeurIPS 2023Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities
- NeurIPS 2023Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time
- NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
- NeurIPS 2023Convolutional Neural Operators for robust and accurate learning of PDEs
- NeurIPS 2023Corruption-Robust Offline Reinforcement Learning with General Function Approximation
- NeurIPS 2023Creating a Public Repository for Joining Private Data
- NeurIPS 2023CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation
- NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
- NeurIPS 2023D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
- NeurIPS 2023Data-Informed Geometric Space Selection
- NeurIPS 2023Debiased and Denoised Entity Recognition from Distant Supervision
- NeurIPS 2023Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
- NeurIPS 2023Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
- NeurIPS 2023Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
- NeurIPS 2023Delegated Classification
- NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
- NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
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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.