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 52 of 54

2551. NeurIPS 2023Model Shapley: Equitable Model Valuation with Black-box Access
2552. NeurIPS 2023Model Sparsity Can Simplify Machine Unlearning
2553. NeurIPS 2023Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation
2554. NeurIPS 2023Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization
2555. NeurIPS 2023Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation
2556. NeurIPS 2023Mutual Information Regularized Offline Reinforcement Learning
2557. NeurIPS 2023Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
2558. NeurIPS 2023Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
2559. NeurIPS 2023Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
2560. NeurIPS 2023Neural Modulation for Flash Memory: An Unsupervised Learning Framework for Improved Reliability
2561. NeurIPS 2023NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function
2562. NeurIPS 2023No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand
2563. NeurIPS 2023Nonparametric Teaching for Multiple Learners
2564. NeurIPS 2023OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
2565. NeurIPS 2023Object-centric Learning with Cyclic Walks between Parts and Whole
2566. NeurIPS 2023Object-Centric Slot Diffusion
2567. NeurIPS 2023On Proper Learnability between Average- and Worst-case Robustness
2568. NeurIPS 2023On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds
2569. NeurIPS 2023On skip connections and normalisation layers in deep optimisation
2570. NeurIPS 2023On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
2571. NeurIPS 2023On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
2572. NeurIPS 2023On the Interplay between Social Welfare and Tractability of Equilibria
2573. NeurIPS 2023On the Robustness of Removal-Based Feature Attributions
2574. NeurIPS 2023On the Role of Entanglement and Statistics in Learning
2575. NeurIPS 2023One Fits All: Power General Time Series Analysis by Pretrained LM
2576. NeurIPS 2023Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
2577. NeurIPS 2023Operator Learning with Neural Fields: Tackling PDEs on General Geometries
2578. NeurIPS 2023Optimal and Fair Encouragement Policy Evaluation and Learning
2579. NeurIPS 2023Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
2580. NeurIPS 2023Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection
2581. NeurIPS 2023Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
2582. NeurIPS 2023Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond $1+\alpha$ Moments
2583. NeurIPS 2023Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation
2584. NeurIPS 2023Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies
2585. NeurIPS 2023Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
2586. NeurIPS 2023Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
2587. NeurIPS 2023Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage
2588. NeurIPS 2023Partial Multi-Label Learning with Probabilistic Graphical Disambiguation
2589. NeurIPS 2023PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
2590. NeurIPS 2023Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
2591. NeurIPS 2023PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
2592. NeurIPS 2023Posterior Sampling for Competitive RL: Function Approximation and Partial Observation
2593. NeurIPS 2023Practical Differentially Private Hyperparameter Tuning with Subsampling
2594. NeurIPS 2023Prediction and Control in Continual Reinforcement Learning
2595. NeurIPS 2023Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
2596. NeurIPS 2023Promises and Pitfalls of Threshold-based Auto-labeling
2597. NeurIPS 2023Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization
2598. NeurIPS 2023Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability
2599. NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
2600. NeurIPS 2023ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction

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.