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

670 papers, page 5 of 14

201. ICLR 2025Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
202. ICLR 2025Vertical Federated Learning with Missing Features During Training and Inference
203. ICLR 2025What should a neuron aim for? Designing local objective functions based on information theory
204. ICLR 2025When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
205. ICLR 2025Wide Neural Networks Trained with Weight Decay Provably Exhibit Neural Collapse
206. ICML 2025$\mathcal{V}ista\mathcal{DPO}$: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models
207. ICML 2025A Bregman Proximal Viewpoint on Neural Operators
208. ICML 2025A Generalization Result for Convergence in Learning-to-Optimize
209. ICML 2025A Near Linear Query Lower Bound for Submodular Maximization
210. ICML 2025A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
211. ICML 2025A Parametric Contextual Online Learning Theory of Brokerage
212. ICML 2025A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
213. ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
214. ICML 2025Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
215. ICML 2025Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
216. ICML 2025Aligned Multi Objective Optimization
217. ICML 2025An in depth look at the Procrustes-Wasserstein distance: properties and barycenters
218. ICML 2025Analytical Lyapunov Function Discovery: An RL-based Generative Approach
219. ICML 2025Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
220. ICML 2025Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
221. ICML 2025Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
222. ICML 2025Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
223. ICML 2025Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts
224. ICML 2025Compact Matrix Quantum Group Equivariant Neural Networks
225. ICML 2025Competitively Consistent Clustering
226. ICML 2025Consensus Is All You Get: The Role of Attention in Transformers
227. ICML 2025Constrained Online Convex Optimization with Polyak Feasibility Steps
228. ICML 2025Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
229. ICML 2025Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
230. ICML 2025Decoupled SGDA for Games with Intermittent Strategy Communication
231. ICML 2025Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
232. ICML 2025Differentiable Quadratic Optimization For the Maximum Independent Set Problem
233. ICML 2025Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
234. ICML 2025Dimension-Free Adaptive Subgradient Methods with Frequent Directions
235. ICML 2025Discrepancy Minimization in Input-Sparsity Time
236. ICML 2025Distributed Conformal Prediction via Message Passing
237. ICML 2025Distributed Event-Based Learning via ADMM
238. ICML 2025Dueling Convex Optimization with General Preferences
239. ICML 2025Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
240. ICML 2025Efficient Distributed Optimization under Heavy-Tailed Noise
241. ICML 2025Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
242. ICML 2025Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
243. ICML 2025End-to-End Learning Framework for Solving Non-Markovian Optimal Control
244. ICML 2025Enforcing Idempotency in Neural Networks
245. ICML 2025Enhancing Performance of Explainable AI Models with Constrained Concept Refinement
246. ICML 2025Ensemble Learned Bloom Filters: Two Oracles are Better than One
247. ICML 2025Exact risk curves of signSGD in High-Dimensions: quantifying preconditioning and noise-compression effects
248. ICML 2025Expected Variational Inequalities
249. ICML 2025Exploiting Curvature in Online Convex Optimization with Delayed Feedback
250. ICML 2025Exploiting Similarity for Computation and Communication-Efficient Decentralized 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.