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

778 papers, page 4 of 16

151. NeurIPS 2025An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models
152. NeurIPS 2025An Ellipsoid Algorithm for Online Convex Optimization
153. NeurIPS 2025Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions
154. NeurIPS 2025Any-stepsize Gradient Descent for Separable Data under Fenchel–Young Losses
155. NeurIPS 2025Approximation theory for 1-Lipschitz ResNets
156. NeurIPS 2025ASGO: Adaptive Structured Gradient Optimization
157. NeurIPS 2025Attention-based clustering
158. NeurIPS 2025Autoencoding Random Forests
159. NeurIPS 2025Balancing Gradient and Hessian Queries in Non-Convex Optimization
160. NeurIPS 2025Bayesian Optimization with Preference Exploration using a Monotonic Neural Network Ensemble
161. NeurIPS 2025Benign Overfitting in Single-Head Attention
162. NeurIPS 2025Better NTK Conditioning: A Free Lunch from (ReLU) Nonlinear Activation in Wide Neural Networks
163. NeurIPS 2025Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
164. NeurIPS 2025Beyond Value Functions: Single-Loop Bilevel Optimization under Flatness Conditions
165. NeurIPS 2025Bilevel Optimization for Adversarial Learning Problems: Sharpness, Generation, and Beyond
166. NeurIPS 2025Block Coordinate Descent for Neural Networks Provably Finds Global Minima
167. NeurIPS 2025Bootstrap Your Uncertainty: Adaptive Robust Classification Driven by Optimal-Transport
168. NeurIPS 2025Bridging Scales: Spectral Theory Reveals How Local Connectivity Rules Sculpt Global Neural Dynamics in Spatially Extended Networks
169. NeurIPS 2025CAMO: Convergence-Aware Multi-Fidelity Bayesian Optimization
170. NeurIPS 2025Can Diffusion Models Disentangle? A Theoretical Perspective
171. NeurIPS 2025CATransformers: Carbon Aware Transformers Through Joint Model-Hardware Optimization
172. NeurIPS 2025Combinatorial Ski Rental Problem: Robust and Learning-Augmented Algorithms
173. NeurIPS 2025Conditional Gradient Methods with Standard LMO for Stochastic Simple Bilevel Optimization
174. NeurIPS 2025Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees
175. NeurIPS 2025Constrained Linear Thompson Sampling
176. NeurIPS 2025Constrained Optimization From a Control Perspective via Feedback Linearization
177. NeurIPS 2025Contextual Dynamic Pricing with Heterogeneous Buyers
178. NeurIPS 2025Continuous Subspace Optimization for Continual Learning
179. NeurIPS 2025Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space
180. NeurIPS 2025Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization
181. NeurIPS 2025Convergence of Clipped SGD on Convex $(L_0,L_1)$-Smooth Functions
182. NeurIPS 2025Convergence of the Gradient Flow for Shallow ReLU Networks on Weakly Interacting Data
183. NeurIPS 2025Convergence Rates for Gradient Descent on the Edge of Stability for Overparametrised Least Squares
184. NeurIPS 2025Convergence Rates of Constrained Expected Improvement
185. NeurIPS 2025Coreset for Robust Geometric Median: Eliminating Size Dependency on Outliers
186. NeurIPS 2025Corporate Needs You to Find the Difference: Revisiting Submodular and Supermodular Ratio Optimization Problems
187. NeurIPS 2025Cyclic Counterfactuals under Shift–Scale Interventions
188. NeurIPS 2025Decreasing Entropic Regularization Averaged Gradient for Semi-Discrete Optimal Transport
189. NeurIPS 2025Deep learning for continuous-time stochastic control with jumps
190. NeurIPS 2025Deep Legendre Transform
191. NeurIPS 2025Deployment Efficient Reward-Free Exploration with Linear Function Approximation
192. NeurIPS 2025DesignX: Human-Competitive Algorithm Designer for Black-Box Optimization
193. NeurIPS 2025Differentiable extensions with rounding guarantees for combinatorial optimization over permutations
194. NeurIPS 2025Differentiation Through Black-Box Quadratic Programming Solvers
195. NeurIPS 2025Dimension-adapted Momentum Outscales SGD
196. NeurIPS 2025Disentangling Hyperedges through the Lens of Category Theory
197. NeurIPS 2025Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences?
198. NeurIPS 2025Distribution-Aware Tensor Decomposition for Compression of Convolutional Neural Networks
199. NeurIPS 2025Distributionally Robust Feature Selection
200. NeurIPS 2025Distributionally Robust Performative Optimization

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.