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

463 papers, page 5 of 10

201. ICML 2026Towards Understanding Adam Convergence on Highly Degenerate Polynomials
202. ICML 2026Towards Understanding Generalization of Federated Adversarial Learning: Perspective of Algorithmic Stability
203. ICML 2026Trainable Nonexpansive Denoisers for Contractive Image Reconstruction
204. ICML 2026Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs
205. ICML 2026TSP with Predictions: Heatmap to Tour with Provable Guarantees
206. ICML 2026Understanding MARS: When Scaling Momentum Provably Helps
207. ICML 2026Understanding SAM through Minimax Perspective
208. ICML 2026Universal Learning of Nonlinear Dynamics
209. ICML 2026Universal Representation of Generalized Convex Functions and their Gradients
210. ICML 2026Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets
211. ICML 2026Variance-Reduced $(\varepsilon, \delta)-$Unlearning using Forget Set Gradients
212. ICML 2026What Does Preference Learning Recover from Pairwise Comparison Data?
213. ICML 2026What Does Thompson Sampling Optimize?
214. ICML 2026Why Do We Need Warm-up? A Theoretical Perspective
215. ICML 2025$\mathcal{V}ista\mathcal{DPO}$: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models
216. ICML 2025A Bregman Proximal Viewpoint on Neural Operators
217. ICML 2025A Generalization Result for Convergence in Learning-to-Optimize
218. ICML 2025A Near Linear Query Lower Bound for Submodular Maximization
219. ICML 2025A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
220. ICML 2025A Parametric Contextual Online Learning Theory of Brokerage
221. ICML 2025A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
222. ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
223. ICML 2025Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
224. ICML 2025Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
225. ICML 2025Aligned Multi Objective Optimization
226. ICML 2025An in depth look at the Procrustes-Wasserstein distance: properties and barycenters
227. ICML 2025Analytical Lyapunov Function Discovery: An RL-based Generative Approach
228. ICML 2025Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
229. ICML 2025Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
230. ICML 2025Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
231. ICML 2025Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
232. ICML 2025Certifiably Robust Model Evaluation in Federated Learning under Meta-Distributional Shifts
233. ICML 2025Compact Matrix Quantum Group Equivariant Neural Networks
234. ICML 2025Competitively Consistent Clustering
235. ICML 2025Consensus Is All You Get: The Role of Attention in Transformers
236. ICML 2025Constrained Online Convex Optimization with Polyak Feasibility Steps
237. ICML 2025Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
238. ICML 2025Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
239. ICML 2025Decoupled SGDA for Games with Intermittent Strategy Communication
240. ICML 2025Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions
241. ICML 2025Differentiable Quadratic Optimization For the Maximum Independent Set Problem
242. ICML 2025Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
243. ICML 2025Dimension-Free Adaptive Subgradient Methods with Frequent Directions
244. ICML 2025Discrepancy Minimization in Input-Sparsity Time
245. ICML 2025Distributed Conformal Prediction via Message Passing
246. ICML 2025Distributed Event-Based Learning via ADMM
247. ICML 2025Dueling Convex Optimization with General Preferences
248. ICML 2025Efficient Curvature-Aware Hypergradient Approximation for Bilevel Optimization
249. ICML 2025Efficient Distributed Optimization under Heavy-Tailed Noise
250. ICML 2025Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance

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.