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

609 papers, page 10 of 13

451. ICLR 2024Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
452. ICLR 2024Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
453. ICLR 2024Accelerating Sinkhorn algorithm with sparse Newton iterations
454. ICLR 2024Adaptive Federated Learning with Auto-Tuned Clients
455. ICLR 2024Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
456. ICLR 2024Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
457. ICLR 2024An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment
458. ICLR 2024An improved analysis of per-sample and per-update clipping in federated learning
459. ICLR 2024Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization
460. ICLR 2024Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate
461. ICLR 2024Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
462. ICLR 2024CO2: Efficient Distributed Training with Full Communication-Computation Overlap
463. ICLR 2024Combining Axes Preconditioners through Kronecker Approximation for Deep Learning
464. ICLR 2024Communication-Efficient Federated Non-Linear Bandit Optimization
465. ICLR 2024Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
466. ICLR 2024Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm
467. ICLR 2024Contextual Bandits with Online Neural Regression
468. ICLR 2024Convergence of Bayesian Bilevel Optimization
469. ICLR 2024Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
470. ICLR 2024Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality
471. ICLR 2024Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
472. ICLR 2024Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
473. ICLR 2024DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training
474. ICLR 2024Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
475. ICLR 2024Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
476. ICLR 2024Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
477. ICLR 2024Distributionally Robust Optimization with Bias and Variance Reduction
478. ICLR 2024Doubly Robust Instance-Reweighted Adversarial Training
479. ICLR 2024Dropout Enhanced Bilevel Training
480. ICLR 2024EControl: Fast Distributed Optimization with Compression and Error Control
481. ICLR 2024Efficient Continual Finite-Sum Minimization
482. ICLR 2024Efficiently Computing Similarities to Private Datasets
483. ICLR 2024Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants
484. ICLR 2024Fantastic Generalization Measures are Nowhere to be Found
485. ICLR 2024Fast Equilibrium of SGD in Generic Situations
486. ICLR 2024FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
487. ICLR 2024Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
488. ICLR 2024Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem
489. ICLR 2024FOSI: Hybrid First and Second Order Optimization
490. ICLR 2024General Stability Analysis for Zeroth-Order Optimization Algorithms
491. ICLR 2024Generative Adversarial Equilibrium Solvers
492. ICLR 2024GIO: Gradient Information Optimization for Training Dataset Selection
493. ICLR 2024Global Optimality for Non-linear Constrained Restoration Problems via Invexity
494. ICLR 2024Grokking as the transition from lazy to rich training dynamics
495. ICLR 2024How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
496. ICLR 2024How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation
497. ICLR 2024Implicit regularization of deep residual networks towards neural ODEs
498. ICLR 2024Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data
499. ICLR 2024Improving Convergence and Generalization Using Parameter Symmetries
500. ICLR 2024Improving equilibrium propagation without weight symmetry through Jacobian homeostasis

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.