Theory · online learning papers, 2023–2026

Key findings

• Theory · online learning went from 164 papers in 2023 to 190 in 2026, roughly 1.2x in three years.
• NeurIPS publishes the most Theory · online learning work: 427 papers from 2023 to 2026, 56% of the four-venue total.
• The fastest-growing overlap is with Simulation for Driving: papers tagged with both rose from 1 in 2023 to 12 in 2026.
• Among the 5 topics under Theory and Statistics, it ranks #3 by 2026 paper count; the fastest grower in the group, Theory · learning theory, is up 5.6x versus 1.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Single-Sample Polylogarithmic Regret Bound for Nonstationary Online Linear Programming
• ICML 2026A Perturbation Approach to Unconstrained Linear Bandits
• ICLR 2026Rethinking Data Curation in LLM Training: Online Reweighting Offers Better Generalization than Offline Methods
• CVPR 2026An Optimal Transport-driven Approach for Cultivating Latent Space in Online
• NeurIPS 2025A Learning-Augmented Approach to Online Allocation Problems
• ICML 2025A Classification View on Meta Learning Bandits
• ICLR 2025Efficient Online Pruning and Abstraction for Imperfect Information Extensive-Form Games
• CVPR 2025InteractionMap: Improving Online Vectorized HDMap Construction with Interaction
• NeurIPS 2024A Best-of-both-worlds Algorithm for Bandits with Delayed Feedback with Robustness to Excessive Delays
• ICML 2024On Online Experimentation without Device Identifiers
• ICLR 2024Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning
• CVPR 2024Dual-Enhanced Coreset Selection with Class-wise Collaboration for Online Blurry Class Incremental Learning
• NeurIPS 2023$\varepsilon$-fractional core stability in Hedonic Games.
• ICML 2023Applied Online Algorithms with Heterogeneous Predictors
• ICLR 2023Hebbian Deep Learning Without Feedback
• CVPR 2023VisFusion: Visibility-Aware Online 3D Scene Reconstruction From Videos
• NeurIPS 2026A Theory of Adversary-Directed Online Learning
• ICML 2026A Two-Layer Framework for Joint Online Configuration Selection and Admission Control
• ICLR 2026A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers
• CVPR 2026Dynamic Momentum Recalibration in Online Gradient Learning

All Theory · online learning papers

101 papers, page 2 of 3

51. NeurIPS 2023Online Control for Meta-optimization
52. NeurIPS 2023Online Convex Optimization with Unbounded Memory
53. NeurIPS 2023Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization
54. NeurIPS 2023Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
55. NeurIPS 2023Online learning of long-range dependencies
56. NeurIPS 2023Online Learning under Adversarial Nonlinear Constraints
57. NeurIPS 2023Online List Labeling with Predictions
58. NeurIPS 2023Online Nonstochastic Model-Free Reinforcement Learning
59. NeurIPS 2023Online PCA in Converging Self-consistent Field Equations
60. NeurIPS 2023Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games
61. NeurIPS 2023Online Pricing for Multi-User Multi-Item Markets
62. NeurIPS 2023Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore
63. NeurIPS 2023Online robust non-stationary estimation
64. NeurIPS 2023Optimal Learners for Realizable Regression: PAC Learning and Online Learning
65. NeurIPS 2023Optimal Rates for Bandit Nonstochastic Control
66. NeurIPS 2023Optimistic Meta-Gradients
67. NeurIPS 2023Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL
68. NeurIPS 2023Partial Matrix Completion
69. NeurIPS 2023Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint
70. NeurIPS 2023Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties
71. NeurIPS 2023Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data
72. NeurIPS 2023Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games
73. NeurIPS 2023Practical Contextual Bandits with Feedback Graphs
74. NeurIPS 2023Projection-Free Online Convex Optimization via Efficient Newton Iterations
75. NeurIPS 2023Quantifying & Modeling Multimodal Interactions: An Information Decomposition Framework
76. NeurIPS 2023Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time
77. NeurIPS 2023Reliable learning in challenging environments
78. NeurIPS 2023Replicable Clustering
79. NeurIPS 2023Residual Q-Learning: Offline and Online Policy Customization without Value
80. NeurIPS 2023Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning
81. NeurIPS 2023Riemannian Projection-free Online Learning
82. NeurIPS 2023Robust Knowledge Transfer in Tiered Reinforcement Learning
83. NeurIPS 2023Selective Sampling and Imitation Learning via Online Regression
84. NeurIPS 2023Sharp Spectral Rates for Koopman Operator Learning
85. NeurIPS 2023Smoothed Analysis of Sequential Probability Assignment
86. NeurIPS 2023Smoothed Online Learning for Prediction in Piecewise Affine Systems
87. NeurIPS 2023Strategic Apple Tasting
88. NeurIPS 2023Strategic Classification under Unknown Personalized Manipulation
89. NeurIPS 2023Strategic Data Sharing between Competitors
90. NeurIPS 2023Structured Prediction with Stronger Consistency Guarantees
91. NeurIPS 2023Supervised Pretraining Can Learn In-Context Reinforcement Learning
92. NeurIPS 2023The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
93. NeurIPS 2023The Gain from Ordering in Online Learning
94. NeurIPS 2023Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games
95. NeurIPS 2023Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning
96. NeurIPS 2023Two-Stage Learning to Defer with Multiple Experts
97. NeurIPS 2023Unconstrained Dynamic Regret via Sparse Coding
98. NeurIPS 2023Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
99. NeurIPS 2023Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies
100. NeurIPS 2023When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment

FAQ

How many Theory · online learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

763 in total: 164 in 2023, 224 in 2024, 185 in 2025, 190 in 2026.

How many Theory · online learning papers are at NeurIPS 2026?

NeurIPS 2026 has 68 Theory · online learning papers, versus 89 the year before.

How many Theory · online learning papers are at ICLR 2026?

ICLR 2026 has 27 Theory · online learning papers, versus 18 the year before.

How many Theory · online learning papers are at ICML 2026?

ICML 2026 has 86 Theory · online learning papers, versus 74 the year before.

How many Theory · online learning papers are at CVPR 2026?

CVPR 2026 has 9 Theory · online learning papers, versus 4 the year before.

Which conference publishes the most Theory · online learning papers?

NeurIPS, with 427 papers from 2023 to 2026.