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 7 of 16

301. NeurIPS 2025Neural Combinatorial Optimization for Time Dependent Traveling Salesman Problem
302. NeurIPS 2025Neural Evolution Strategy for Black-box Pareto Set Learning
303. NeurIPS 2025New Parallel and Streaming Algorithms for Directed Densest Subgraph
304. NeurIPS 2025New Perspectives on the Polyak Stepsize: Surrogate Functions and Negative Results
305. NeurIPS 2025Non-Clairvoyant Scheduling with Progress Bars
306. NeurIPS 2025Non-convex entropic mean-field optimization via Best Response flow
307. NeurIPS 2025Non-Convex Tensor Recovery from Tube-Wise Sensing
308. NeurIPS 2025Non-monotone Submodular Optimization: $p$-Matchoid Constraints and Fully Dynamic Setting
309. NeurIPS 2025Non-Singularity of the Gradient Descent Map for Neural Networks with Piecewise Analytic Activations
310. NeurIPS 2025Non-stationary Bandit Convex Optimization: A Comprehensive Study
311. NeurIPS 2025Non-Stationary Lipschitz Bandits
312. NeurIPS 2025Nonlinear Laplacians: Tunable principal component analysis under directional prior information
313. NeurIPS 2025Nonlinearly Preconditioned Gradient Methods: Momentum and Stochastic Analysis
314. NeurIPS 2025NPN: Non-Linear Projections of the Null-Space for Imaging Inverse Problems
315. NeurIPS 2025Nyström-Accelerated Primal LS-SVMs: Breaking the $O(an^3)$ Complexity Bottleneck for Scalable ODEs Learning
316. NeurIPS 2025On Extending Direct Preference Optimization to Accommodate Ties
317. NeurIPS 2025On Linear Mode Connectivity of Mixture-of-Experts Architectures
318. NeurIPS 2025On the $O(\frac{\sqrt{d}}{K^{1/4}})$ Convergence Rate of AdamW Measured by $\ell_1$ Norm
319. NeurIPS 2025On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization
320. NeurIPS 2025On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent
321. NeurIPS 2025On the Emergence of Linear Analogies in Word Embeddings
322. NeurIPS 2025On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
323. NeurIPS 2025On the Robustness of Transformers against Context Hijacking for Linear Classification
324. NeurIPS 2025On the sample complexity of semi-supervised multi-objective learning
325. NeurIPS 2025On Traceability in $\ell_p$ Stochastic Convex Optimization
326. NeurIPS 2025On Transferring Transferability: Towards a Theory for Size Generalization
327. NeurIPS 2025On Universality Classes of Equivariant Networks
328. NeurIPS 2025Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound
329. NeurIPS 2025Online Multi-Class Selection with Group Fairness Guarantee
330. NeurIPS 2025Online Portfolio Selection with ML Predictions
331. NeurIPS 2025Online Two-Stage Submodular Maximization
332. NeurIPS 2025Opinion Maximization in Social Networks by Modifying Internal Opinions
333. NeurIPS 2025OPTFM: A Scalable Multi-View Graph Transformer for Hierarchical Pre-Training in Combinatorial Optimization
334. NeurIPS 2025Optimal Rates for Generalization of Gradient Descent for Deep ReLU Classification
335. NeurIPS 2025Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions
336. NeurIPS 2025Optimistic Online-to-Batch Conversions for Accelerated Convergence and Universality
337. NeurIPS 2025Optimizing the Unknown: Black Box Bayesian Optimization with Energy-Based Model and Reinforcement Learning
338. NeurIPS 2025Oracle-Efficient Combinatorial Semi-Bandits
339. NeurIPS 2025Parameter-free Algorithms for the Stochastically Extended Adversarial Model
340. NeurIPS 2025Partial Correlation Network Estimation by Semismooth Newton Methods
341. NeurIPS 2025Pause Tokens Strictly Increase the Expressivity of Constant-Depth Transformers
342. NeurIPS 2025PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs
343. NeurIPS 2025PDPO: Parametric Density Path Optimization
344. NeurIPS 2025Perturbation Bounds for Low-Rank Inverse Approximations under Noise
345. NeurIPS 2025PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts
346. NeurIPS 2025Predictability Enables Parallelization of Nonlinear State Space Models
347. NeurIPS 2025Preference Optimization on Pareto Sets: On a Theory of Multi-Objective Optimization
348. NeurIPS 2025Price of Parsimony: Complexity of Fourier Sparsity Testing
349. NeurIPS 2025Probing Neural Combinatorial Optimization Models
350. NeurIPS 2025Problem-Parameter-Free Decentralized Bilevel 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.