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 11 of 16

501. NeurIPS 2024Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits
502. NeurIPS 2024Directional Smoothness and Gradient Methods: Convergence and Adaptivity
503. NeurIPS 2024Discretely beyond $1/e$: Guided Combinatorial Algortihms for Submodular Maximization
504. NeurIPS 2024Disentangling Linear Quadratic Control with Untrusted ML Predictions
505. NeurIPS 2024Distribution Learning with Valid Outputs Beyond the Worst-Case
506. NeurIPS 2024Distributional Preference Alignment of LLMs via Optimal Transport
507. NeurIPS 2024DistrictNet: Decision-aware learning for geographical districting
508. NeurIPS 2024Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
509. NeurIPS 2024Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD
510. NeurIPS 2024Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences
511. NeurIPS 2024Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
512. NeurIPS 2024Dual Lagrangian Learning for Conic Optimization
513. NeurIPS 2024Efficiency of the First-Price Auction in the Autobidding World
514. NeurIPS 2024Efficient Combinatorial Optimization via Heat Diffusion
515. NeurIPS 2024Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
516. NeurIPS 2024Efficient Leverage Score Sampling for Tensor Train Decomposition
517. NeurIPS 2024Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
518. NeurIPS 2024Emergence of heavy tails in homogenized stochastic gradient descent
519. NeurIPS 2024Euclidean distance compression via deep random features
520. NeurIPS 2024Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
521. NeurIPS 2024Explicit Eigenvalue Regularization Improves Sharpness-Aware Minimization
522. NeurIPS 2024Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
523. NeurIPS 2024Fair Secretaries with Unfair Predictions
524. NeurIPS 2024Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
525. NeurIPS 2024Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
526. NeurIPS 2024Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
527. NeurIPS 2024Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning
528. NeurIPS 2024FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning
529. NeurIPS 2024FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction
530. NeurIPS 2024First-Order Methods for Linearly Constrained Bilevel Optimization
531. NeurIPS 2024First-Order Minimax Bilevel Optimization
532. NeurIPS 2024Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
533. NeurIPS 2024From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization
534. NeurIPS 2024FUGAL: Feature-fortified Unrestricted Graph Alignment
535. NeurIPS 2024Functional Bilevel Optimization for Machine Learning
536. NeurIPS 2024Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem
537. NeurIPS 2024Fundamental Convergence Analysis of Sharpness-Aware Minimization
538. NeurIPS 2024Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models
539. NeurIPS 2024Generalized Fast Exact Conformalization
540. NeurIPS 2024Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables
541. NeurIPS 2024GLinSAT: The General Linear Satisfiability Neural Network Layer By Accelerated Gradient Descent
542. NeurIPS 2024Gradient Guidance for Diffusion Models: An Optimization Perspective
543. NeurIPS 2024Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
544. NeurIPS 2024Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization
545. NeurIPS 2024Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame
546. NeurIPS 2024Hardness of Learning Neural Networks under the Manifold Hypothesis
547. NeurIPS 2024High-probability complexity bounds for stochastic non-convex minimax optimization
548. NeurIPS 2024How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization?
549. NeurIPS 2024How does Gradient Descent Learn Features --- A Local Analysis for Regularized Two-Layer Neural Networks
550. NeurIPS 2024How Sparse Can We Prune A Deep Network: A Fundamental Limit Perspective

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.