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

670 papers, page 2 of 14

51. ICLR 2025Convex Formulations for Training Two-Layer ReLU Neural Networks
52. ICLR 2025Debiasing Federated Learning with Correlated Client Participation
53. ICLR 2025Debiasing Mini-Batch Quadratics for Applications in Deep Learning
54. ICLR 2025dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation
55. ICLR 2025Decentralized Optimization with Coupled Constraints
56. ICLR 2025Decision Information Meets Large Language Models: The Future of Explainable Operations Research
57. ICLR 2025Decision Tree Induction Through LLMs via Semantically-Aware Evolution
58. ICLR 2025Decoding Game: On Minimax Optimality of Heuristic Text Generation Strategies
59. ICLR 2025Decomposition Polyhedra of Piecewise Linear Functions
60. ICLR 2025Deep Distributed Optimization for Large-Scale Quadratic Programming
61. ICLR 2025DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance
62. ICLR 2025Descent with Misaligned Gradients and Applications to Hidden Convexity
63. ICLR 2025Direct Distributional Optimization for Provable Alignment of Diffusion Models
64. ICLR 2025Do Deep Neural Network Solutions Form a Star Domain?
65. ICLR 2025Do Stochastic, Feel Noiseless: Stable Stochastic Optimization via a Double Momentum Mechanism
66. ICLR 2025Does SGD really happen in tiny subspaces?
67. ICLR 2025DON’T STOP ME NOW: EMBEDDING BASED SCHEDULING FOR LLMS
68. ICLR 2025DRoC: Elevating Large Language Models for Complex Vehicle Routing via Decomposed Retrieval of Constraints
69. ICLR 2025DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity
70. ICLR 2025Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation
71. ICLR 2025Efficient Interpolation between Extragradient and Proximal Methods for Weak MVIs
72. ICLR 2025Efficient Sparse PCA via Block-Diagonalization
73. ICLR 2025Efficient stagewise pretraining via progressive subnetworks
74. ICLR 2025Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures
75. ICLR 2025Entropy-based Activation Function Optimization: A Method on Searching Better Activation Functions
76. ICLR 2025Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality
77. ICLR 2025Fair Submodular Cover
78. ICLR 2025Faster Algorithms for Structured Linear and Kernel Support Vector Machines
79. ICLR 2025Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
80. ICLR 2025Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
81. ICLR 2025FLOPS: Forward Learning with OPtimal Sampling
82. ICLR 2025From Decoupling to Adaptive Transformation: a Wider Optimization Space for PTQ
83. ICLR 2025From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
84. ICLR 2025GeoLoRA: Geometric integration for parameter efficient fine-tuning
85. ICLR 2025Geometric Inductive Biases of Deep Networks: The Role of Data and Architecture
86. ICLR 2025Gradient correlation is a key ingredient to accelerate SGD with momentum
87. ICLR 2025Gradient descent with generalized Newton’s method
88. ICLR 2025Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
89. ICLR 2025Group Distributionally Robust Dataset Distillation with Risk Minimization
90. ICLR 2025How Gradient descent balances features: A dynamical analysis for two-layer neural networks
91. ICLR 2025How many samples are needed to train a deep neural network?
92. ICLR 2025How Much is Unseen Depends Chiefly on Information About the Seen
93. ICLR 2025Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression
94. ICLR 2025Improved Approximation Algorithms for $k$-Submodular Maximization via Multilinear Extension
95. ICLR 2025Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
96. ICLR 2025Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization
97. ICLR 2025LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
98. ICLR 2025Lasso Bandit with Compatibility Condition on Optimal Arm
99. ICLR 2025Last Iterate Convergence of Incremental Methods as a Model of Forgetting
100. ICLR 2025LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics

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.