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

1,871 papers, page 22 of 38

1051. NeurIPS 2025FSEO: Few-Shot Evolutionary Optimization via Meta-Learning for Expensive Multi-Objective Optimization
1052. NeurIPS 2025FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
1053. NeurIPS 2025Gaussian Approximation and Concentration of Constant Learning-Rate Stochastic Gradient Descent
1054. NeurIPS 2025Gaussian Process Upper Confidence Bound Achieves Nearly-Optimal Regret in Noise-Free Gaussian Process Bandits
1055. NeurIPS 2025Generalization Guarantees for Learning Score-Based Branch-and-Cut Policies in Integer Programming
1056. NeurIPS 2025Generalized Gradient Norm Clipping & Non-Euclidean $(L_0,L_1)$-Smoothness
1057. NeurIPS 2025GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility
1058. NeurIPS 2025Global Minimizers of $\ell^p$-Regularized Objectives Yield the Sparsest ReLU Neural Networks
1059. NeurIPS 2025Globally Optimal Policy Gradient Algorithms for Reinforcement Learning with PID Control Policies
1060. NeurIPS 2025Gradient Descent as Loss Landscape Navigation: a Normative Framework for Deriving Learning Rules
1061. NeurIPS 2025Gradient-Variation Online Adaptivity for Accelerated Optimization with Hölder Smoothness
1062. NeurIPS 2025Guarantees for Alternating Least Squares in Overparameterized Tensor Decompositions
1063. NeurIPS 2025Hamiltonian Descent Algorithms for Optimization: Accelerated Rates via Randomized Integration Time
1064. NeurIPS 2025HEIR: Learning Graph-Based Motion Hierarchies
1065. NeurIPS 2025Hephaestus: Mixture Generative Modeling with Energy Guidance for Large-scale QoS Degradation
1066. NeurIPS 2025Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
1067. NeurIPS 2025Heterogeneous Graph Transformers for Simultaneous Mobile Multi-Robot Task Allocation and Scheduling under Temporal Constraints
1068. NeurIPS 2025Hierarchical Demonstration Order Optimization for Many-shot In-Context Learning
1069. NeurIPS 2025Hierarchical Optimization via LLM-Guided Objective Evolution for Mobility-on-Demand Systems
1070. NeurIPS 2025High-Dimensional Calibration from Swap Regret
1071. NeurIPS 2025High-Performance Arithmetic Circuit Optimization via Differentiable Architecture Search
1072. NeurIPS 2025How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
1073. NeurIPS 2025How Memory in Optimization Algorithms Implicitly Modifies the Loss
1074. NeurIPS 2025How Particle System Theory Enhances Hypergraph Message Passing
1075. NeurIPS 2025How to Learn a Star: Binary Classification with Starshaped Polyhedral Sets
1076. NeurIPS 2025How to Scale Second-Order Optimization
1077. NeurIPS 2025Hybrid-Balance GFlowNet for Solving Vehicle Routing Problems
1078. NeurIPS 2025IMPACT: Irregular Multi-Patch Adversarial Composition Based on Two‑Phase Optimization
1079. NeurIPS 2025Improved Algorithms for Fair Matroid Submodular Maximization
1080. NeurIPS 2025Improved Balanced Classification with Theoretically Grounded Loss Functions
1081. NeurIPS 2025Improved Regret Bounds for Gaussian Process Upper Confidence Bound in Bayesian Optimization
1082. NeurIPS 2025Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning
1083. NeurIPS 2025Instance-Dependent Regret Bounds for Nonstochastic Linear Partial Monitoring
1084. NeurIPS 2025Isotropic Noise in Stochastic and Quantum Convex Optimization
1085. NeurIPS 2025Kernel von Mises Formula of the Influence Function
1086. NeurIPS 2025Knee-Deep in C-RASP: A Transformer Depth Hierarchy
1087. NeurIPS 2025KOALA++: Efficient Kalman-Based Optimization with Gradient-Covariance Products
1088. NeurIPS 2025Large Stepsizes Accelerate Gradient Descent for Regularized Logistic Regression
1089. NeurIPS 2025Last Iterate Convergence in Monotone Mean Field Games
1090. NeurIPS 2025Learning (Approximately) Equivariant Networks via Constrained Optimization
1091. NeurIPS 2025Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Imaging Inverse Problems
1092. NeurIPS 2025Learning Expandable and Adaptable Representations for Continual Learning
1093. NeurIPS 2025Learning from A Single Markovian Trajectory: Optimality and Variance Reduction
1094. NeurIPS 2025Learning from Interval Targets
1095. NeurIPS 2025Learning Linear Attention in Polynomial Time
1096. NeurIPS 2025Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling
1097. NeurIPS 2025Learning Provably Improves the Convergence of Gradient Descent
1098. NeurIPS 2025Learning Theory for Kernel Bilevel Optimization
1099. NeurIPS 2025Learning to Insert for Constructive Neural Vehicle Routing Solver
1100. NeurIPS 2025Learning with Statistical Equality Constraints

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.