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 9 of 16

401. NeurIPS 2025Targeted Maximum Likelihood Learning: An Optimization Perspective
402. NeurIPS 2025The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
403. NeurIPS 2025The Complexity of Finding Local Optima in Contrastive Learning
404. NeurIPS 2025The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games
405. NeurIPS 2025The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
406. NeurIPS 2025The Flood Complex: Large-Scale Persistent Homology on Millions of Points
407. NeurIPS 2025The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks
408. NeurIPS 2025The Persistence of Neural Collapse Despite Low-Rank Bias
409. NeurIPS 2025The Rich and the Simple: On the Implicit Bias of Adam and SGD
410. NeurIPS 2025Theoretical Investigation of Adafactor for Non-Convex Smooth Optimization
411. NeurIPS 2025Tight analyses of first-order methods with error feedback
412. NeurIPS 2025Tight Asymptotics of Extreme Order Statistics
413. NeurIPS 2025Tight High-Probability Bounds for Nonconvex Heavy-Tailed Scenario under Weaker Assumptions
414. NeurIPS 2025Tight Lower Bounds and Improved Convergence in Performative Prediction
415. NeurIPS 2025Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling
416. NeurIPS 2025Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach
417. NeurIPS 2025Tractable Multinomial Logit Contextual Bandits with Non-Linear Utilities
418. NeurIPS 2025Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization
419. NeurIPS 2025TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks
420. NeurIPS 2025Two Heads are Better than One: Simulating Large Transformers with Small Ones
421. NeurIPS 2025UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection
422. NeurIPS 2025Unbalanced Optimal Total Variation Transport: A Theoretical Approach to Spatial Resource Allocation Problems
423. NeurIPS 2025Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback
424. NeurIPS 2025Understanding Data Influence in Reinforcement Finetuning
425. NeurIPS 2025Understanding outer learning rates in Local SGD
426. NeurIPS 2025Understanding Softmax Attention Layers:\\ Exact Mean-Field Analysis on a Toy Problem
427. NeurIPS 2025Uniform Wrappers: Bridging Concave to Quadratizable Functions in Online Optimization
428. NeurIPS 2025UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems
429. NeurIPS 2025Unlocking Dataset Distillation with Diffusion Models
430. NeurIPS 2025Unveiling m-Sharpness Through the Structure of Stochastic Gradient Noise
431. NeurIPS 2025What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
432. NeurIPS 2025What Expressivity Theory Misses: Message Passing Complexity for GNNs
433. NeurIPS 2025What Makes a Reward Model a Good Teacher? An Optimization Perspective
434. NeurIPS 2025When Does Curriculum Learning Help? A Theoretical Perspective
435. NeurIPS 2025When majority rules, minority loses: bias amplification of gradient descent
436. NeurIPS 2025Which Algorithms Have Tight Generalization Bounds?
437. NeurIPS 2025Zeroth-Order Optimization Finds Flat Minima
438. NeurIPS 2024$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
439. NeurIPS 20244+3 Phases of Compute-Optimal Neural Scaling Laws
440. NeurIPS 2024A Combinatorial Algorithm for the Semi-Discrete Optimal Transport Problem
441. NeurIPS 2024A Framework for Bilevel Optimization on Riemannian Manifolds
442. NeurIPS 2024A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization
443. NeurIPS 2024A Primal-Dual-Assisted Penalty Approach to Bilevel Optimization with Coupled Constraints
444. NeurIPS 2024A robust inlier identification algorithm for point cloud registration via $\mathbf{\ell_0}$-minimization
445. NeurIPS 2024A two-scale Complexity Measure for Deep Learning Models
446. NeurIPS 2024Accelerating Matroid Optimization through Fast Imprecise Oracles
447. NeurIPS 2024Accelerating Non-Maximum Suppression: A Graph Theory Perspective
448. NeurIPS 2024Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values
449. NeurIPS 2024Achieving Linear Convergence with Parameter-Free Algorithms in Decentralized Optimization
450. NeurIPS 2024Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes

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.