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

185 papers, page 3 of 4

101. NeurIPS 2025Bandit and Delayed Feedback in Online Structured Prediction
102. NeurIPS 2025Comparing Uniform Price and Discriminatory Multi-Unit Auctions through Regret Minimization
103. NeurIPS 2025Computable universal online learning
104. NeurIPS 2025Conformal Online Learning of Deep Koopman Linear Embeddings
105. NeurIPS 2025Conservative classifiers do consistently well with improving agents: characterizing statistical and online learning
106. NeurIPS 2025Consistency of the $k_n$-nearest neighbor rule under adaptive sampling
107. NeurIPS 2025Contextual Online Pricing with (Biased) Offline Data
108. NeurIPS 2025Dynamic Regret Reduces to Kernelized Static Regret
109. NeurIPS 2025Efficient Last-Iterate Convergence in Solving Extensive-Form Games
110. NeurIPS 2025Efficient Spectral Control of Partially Observed Linear Dynamical Systems
111. NeurIPS 2025Efficient Training-Free Online Routing for High-Volume Multi-LLM Serving
112. NeurIPS 2025Explaining the Law of Supply and Demand via Online Learning
113. NeurIPS 2025Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL
114. NeurIPS 2025Exploring the Noise Robustness of Online Conformal Prediction
115. NeurIPS 2025Fair Matroid Selection
116. NeurIPS 2025Finite Sample Analyses for Continuous-time Linear Systems: System Identification and Online Control
117. NeurIPS 2025From Contextual Combinatorial Semi-Bandits to Bandit List Classification: Improved Sample Complexity with Sparse Rewards
118. NeurIPS 2025Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update
119. NeurIPS 2025Gradient Descent as Loss Landscape Navigation: a Normative Framework for Deriving Learning Rules
120. NeurIPS 2025Gradient-Guided Epsilon Constraint Method for Online Continual Learning
121. NeurIPS 2025High-Dimensional Calibration from Swap Regret
122. NeurIPS 2025HyGen: Efficient LLM Serving via Elastic Online-Offline Request Co-location
123. NeurIPS 2025Imagine Beyond ! Distributionally Robust Autoencoding for State Space Coverage in Online Reinforcement Learning
124. NeurIPS 2025Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards
125. NeurIPS 2025Incentive-Aware Dynamic Resource Allocation under Long-Term Cost Constraints
126. NeurIPS 2025Instance-Dependent Regret Bounds for Nonstochastic Linear Partial Monitoring
127. NeurIPS 2025Kernel conditional tests from learning-theoretic bounds
128. NeurIPS 2025Last-Iterate Convergence of Smooth Regret Matching$^+$ Variants in Learning Nash Equilibria
129. NeurIPS 2025Learning Across the Gap: Hybrid Multi-armed Bandits with Heterogeneous Offline and Online Data
130. NeurIPS 2025Learning Orthogonal Multi-Index Models: A Fine-Grained Information Exponent Analysis
131. NeurIPS 2025Learning Personalized Ad Impact via Contextual Reinforcement Learning under Delayed Rewards
132. NeurIPS 2025Learning Preferences without Interaction for Cooperative AI: A Hybrid Offline-Online Approach
133. NeurIPS 2025Learning-Augmented Algorithms for $k$-median via Online Learning
134. NeurIPS 2025Learning-Augmented Online Bidding in Stochastic Settings
135. NeurIPS 2025Learning-Augmented Online Bipartite Fractional Matching
136. NeurIPS 2025Lyapunov-Stable Adaptive Control for Multimodal Concept Drift
137. NeurIPS 2025Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
138. NeurIPS 2025Minimax Adaptive Online Nonparametric Regression over Besov spaces
139. NeurIPS 2025Near-Optimal Quantum Algorithms for Computing (Coarse) Correlated Equilibria of General-Sum Games
140. NeurIPS 2025Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets
141. NeurIPS 2025Near-Optimal Sample Complexity for Online Constrained MDPs
142. NeurIPS 2025No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!
143. NeurIPS 2025No-Regret Online Autobidding Algorithms in First-price Auctions
144. NeurIPS 2025Non-Clairvoyant Scheduling with Progress Bars
145. NeurIPS 2025Non-stationary Bandit Convex Optimization: A Comprehensive Study
146. NeurIPS 2025Non-Uniform Multiclass Learning with Bandit Feedback
147. NeurIPS 2025On the necessity of adaptive regularisation: Optimal anytime online learning on $\boldsymbol{\ell_p}$-balls
148. NeurIPS 2025On the Universal Near Optimality of Hedge in Combinatorial Settings
149. NeurIPS 2025On Union-Closedness of Language Generation
150. NeurIPS 2025Online Bilateral Trade With Minimal Feedback: Don’t Waste Seller’s Time

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.