Theory · optimization papers, 2023–2026

Key findings

• Theory · optimization went from 123 papers in 2023 to 584 in 2026, roughly 4.7x in three years.
• NeurIPS publishes the most Theory · optimization work: 778 papers from 2023 to 2026, 42% of the four-venue total.
• The fastest-growing overlap is with Low-Rank Adaptation: papers tagged with both rose from 0 in 2023 to 31 in 2026.
• Among the 5 topics under Theory and Statistics, it ranks #1 by 2026 paper count; the fastest grower in the group, Theory · learning theory, is up 5.6x versus 4.7x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Mechanistic Investigation of Theory of Mind in a Large Language Model
• ICML 2026A Direct Second-Order Method for Solving Two-Player Zero-Sum Games
• ICLR 2026A Convergence Analysis of Adaptive Optimizers under Floating-point Quantization
• CVPR 2026TriSim Tri-Dimensional Similarity Modeling with Extreme Value Theory for False-Negative
• NeurIPS 20253BASiL: An Algorithmic Framework for Sparse plus Low-Rank Compression of LLMs
• ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
• ICLR 2025A Coefficient Makes SVRG Effective
• CVPR 2025Dynamic Stereotype Theory Induced Micro-expression Recognition with Oriented Deformation
• NeurIPS 2024A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
• ICML 2024A Statistical Theory of Regularization-Based Continual Learning
• ICLR 2024A Discretization Framework for Robust Contextual Stochastic Optimization
• NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
• ICML 2023Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
• ICLR 2023Adaptive Optimization in the $\infty$-Width Limit
• CVPR 2023Deep Hashing With Minimal-Distance-Separated Hash Centers
• NeurIPS 2026Avoiding Obfuscation with Prover-Estimator Debate
• ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
• ICLR 2026A Memory-Efficient Hierarchical Algorithm for Large-scale Optimal Transport Problems
• CVPR 2026FedAdamom Adaptive Momentum for Improved Generalization in Federated Optimization
• NeurIPS 2025A Beyond-Worst-Case Analysis of Greedy k-means++

All Theory · optimization papers

1,871 papers, page 24 of 38

1151. NeurIPS 2025Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification
1152. NeurIPS 2025Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions
1153. NeurIPS 2025Optimistic Online-to-Batch Conversions for Accelerated Convergence and Universality
1154. NeurIPS 2025Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
1155. NeurIPS 2025Oracle-Efficient Combinatorial Semi-Bandits
1156. NeurIPS 2025Parameter-free Algorithms for the Stochastically Extended Adversarial Model
1157. NeurIPS 2025Partial Correlation Network Estimation by Semismooth Newton Methods
1158. NeurIPS 2025Pause Tokens Strictly Increase the Expressivity of Constant-Depth Transformers
1159. NeurIPS 2025PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs
1160. NeurIPS 2025PDPO: Parametric Density Path Optimization
1161. NeurIPS 2025Perturbation Bounds for Low-Rank Inverse Approximations under Noise
1162. NeurIPS 2025PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts
1163. NeurIPS 2025Predictability Enables Parallelization of Nonlinear State Space Models
1164. NeurIPS 2025Preference Optimization on Pareto Sets: On a Theory of Multi-Objective Optimization
1165. NeurIPS 2025Price of Parsimony: Complexity of Fourier Sparsity Testing
1166. NeurIPS 2025Probing Neural Combinatorial Optimization Models
1167. NeurIPS 2025Problem-Parameter-Free Decentralized Bilevel Optimization
1168. NeurIPS 2025Product Distribution Learning with Imperfect Advice
1169. NeurIPS 2025Provable Meta-Learning with Low-Rank Adaptations
1170. NeurIPS 2025Purest Quantum State Identification
1171. NeurIPS 2025Purity Law for Neural Routing Problem Solvers with Enhanced Generalizability
1172. NeurIPS 2025Quantum Speedups for Minimax Optimization and Beyond
1173. NeurIPS 2025Quasi-Self-Concordant Optimization with $\ell_{\infty}$ Lewis Weights
1174. NeurIPS 2025Reinforcement learning for one-shot DAG scheduling with comparability identification and dense reward
1175. NeurIPS 2025Replicable Distribution Testing
1176. NeurIPS 2025Replicable Online Learning
1177. NeurIPS 2025Rethinking Entropy in Test-Time Adaptation: The Missing Piece from Energy Duality
1178. NeurIPS 2025Rethinking Gradient Step Denoiser: Towards Truly Pseudo-Contractive Operator
1179. NeurIPS 2025Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
1180. NeurIPS 2025Revisiting 1-peer exponential graph for enhancing decentralized learning efficiency
1181. NeurIPS 2025Revisiting Agnostic Boosting
1182. NeurIPS 2025Revisiting Consensus Error: A Fine-grained Analysis of Local SGD under Second-order Data Heterogeneity
1183. NeurIPS 2025Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems
1184. NeurIPS 2025Revisiting Frank-Wolfe for Structured Nonconvex Optimization
1185. NeurIPS 2025Robust Federated Finetuning of LLMs via Alternating Optimization of LoRA
1186. NeurIPS 2025Robustifying Learning-Augmented Caching Efficiently without Compromising 1-Consistency
1187. NeurIPS 2025Robustly Learning Monotone Single-Index Models
1188. NeurIPS 2025SAD Neural Networks: Divergent Gradient Flows and Asymptotic Optimality via o-minimal Structures
1189. NeurIPS 2025Sample-Adaptivity Tradeoff in On-Demand Sampling
1190. NeurIPS 2025Scalable Neural Incentive Design with Parameterized Mean-Field Approximation
1191. NeurIPS 2025Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf’s Law
1192. NeurIPS 2025Second-order Optimization under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits
1193. NeurIPS 2025Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing
1194. NeurIPS 2025Semi-infinite Nonconvex Constrained Min-Max Optimization
1195. NeurIPS 2025Set Smoothness Unlocks Clarke Hyper-stationarity in Bilevel Optimization
1196. NeurIPS 2025Sharp Matrix Empirical Bernstein Inequalities
1197. NeurIPS 2025Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings
1198. NeurIPS 2025Sketched Adaptive Distributed Deep Learning: A Sharp Convergence Analysis
1199. NeurIPS 2025Small Singular Values Matter: A Random Matrix Analysis of Transformer Models
1200. NeurIPS 2025Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraints

FAQ

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

1,871 in total: 123 in 2023, 494 in 2024, 670 in 2025, 584 in 2026.

How many Theory · optimization papers are at NeurIPS 2026?

NeurIPS 2026 has 119 Theory · optimization papers, versus 318 the year before.

How many Theory · optimization papers are at ICLR 2026?

ICLR 2026 has 244 Theory · optimization papers, versus 196 the year before.

How many Theory · optimization papers are at ICML 2026?

ICML 2026 has 214 Theory · optimization papers, versus 147 the year before.

How many Theory · optimization papers are at CVPR 2026?

CVPR 2026 has 7 Theory · optimization papers, versus 9 the year before.

Which conference publishes the most Theory · optimization papers?

NeurIPS, with 778 papers from 2023 to 2026.