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

Papers per year

Papers per venue

Counts by year and venue

General ML · unsupervised and semisupervised learning papers by year and venue
YearNeurIPSICLRICMLCVPRTotal
20233188715787649
202411823611584553
202520317423966682
202619418734870799

Representative papers

Spread across years and venues so every edition shows up

All General ML · unsupervised and semisupervised learning papers

798 papers, page 10 of 16

  1. ICML 2026MoCL: Metabolic Optimization for Curvature-Aware Continual Learning
  2. ICML 2026Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
  3. ICML 2026Multi-View Causal Discovery without Non-Gaussianity: Identifiability and Algorithms
  4. ICML 2026Multimodal Nested Learning for Decoupled and Coordinated Optimization
  5. ICML 2026Multivariate Distributional Reinforcement Learning Using Sliced Divergences
  6. ICML 2026Multiview Self-Representation Learning across Heterogeneous Views
  7. ICML 2026nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
  8. ICML 2026Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
  9. ICML 2026Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains
  10. ICML 2026NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
  11. ICML 2026New Algorithms for Fully-Dynamic k-center with Outliers
  12. ICML 2026Newton-coupled Dual-Teacher Semi-supervised Learning Framework
  13. ICML 2026Noise-Robust Density Estimation for Tabular Data Anomaly Detection
  14. ICML 2026Nonlinear Covariate Balance in Experimental Design
  15. ICML 2026Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
  16. ICML 2026Omitted Variable Bias in Language Models Under Distribution Shift
  17. ICML 2026On Contraction of Sequential and Offset Rademacher Complexities
  18. ICML 2026On Learnability and Disambiguation of Multiclass Partial Concept Classes
  19. ICML 2026On Testing Conditional Mean Independence for Manifold-Valued Data
  20. ICML 2026On the Difficulty of Learning a Meta-network for Training Data Selection
  21. ICML 2026On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach
  22. ICML 2026On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
  23. ICML 2026On the Plasticity and Stability for Post-Training Large Language Models
  24. ICML 2026On the Power of Statistics in Class-Incremental Learning with Pretrained Models
  25. ICML 2026One Batch Is Enough: A Unified Dataset Condensation Framework for General Time Series Analysis
  26. ICML 2026One Coin Has Two Sides: Single Poistive Multi Label Learning from Salient Annotations
  27. ICML 2026One-shot Conditional Sampling: MMD meets Nearest Neighbors
  28. ICML 2026Online Learning and Inference for Cox Proportional Hazards Model Using Renewable Sieve Estimation
  29. ICML 2026OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
  30. ICML 2026Optimal Learning from Label Proportions with General Loss Functions
  31. ICML 2026Optimal structure learning and conditional independence testing
  32. ICML 2026Optimal Top-$k$ Identification from Pairwise Comparisons
  33. ICML 2026Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
  34. ICML 2026OPTION: Optimal Transport–Guided Flow Matching for Incomplete and Unaligned Multi-View Clustering
  35. ICML 2026Orthogonal Model Merging
  36. ICML 2026OvisOCR: End-to-End Document Parsing via Aligning Specialized Perception with General Reasoning
  37. ICML 2026PACE: Parameter Change for Unsupervised Environment Design
  38. ICML 2026PartCo: Part-Level Correspondence Priors Enhance Category Discovery
  39. ICML 2026Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
  40. ICML 2026Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport
  41. ICML 2026PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
  42. ICML 2026Positive-Unlabeled Learning with Extreme Scarcity of Labeled Positives
  43. ICML 2026PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
  44. ICML 2026Powerful and Theoretically Guaranteed Independence Testing on Heterogeneous Federated Clients
  45. ICML 2026Predictive variational inference: Learn the predictively optimal posterior distribution
  46. ICML 2026Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
  47. ICML 2026PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning
  48. ICML 2026Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis
  49. ICML 2026Quantifying Frontier LLM Capabilities for Container Sandbox Escape
  50. ICML 2026Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised 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.

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