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

123 papers, page 2 of 3

51. ICLR 2023Why adversarial training can hurt robust accuracy
52. ICML 2023A Fully First-Order Method for Stochastic Bilevel Optimization
53. ICML 2023A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
54. ICML 2023Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
55. ICML 2023Accelerated Stochastic Optimization Methods under Quasar-convexity
56. ICML 2023Algorithmic Collective Action in Machine Learning
57. ICML 2023Automatically Auditing Large Language Models via Discrete Optimization
58. ICML 2023Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
59. ICML 2023Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization
60. ICML 2023Beyond Uniform Lipschitz Condition in Differentially Private Optimization
61. ICML 2023Bit Allocation using Optimization
62. ICML 2023Certifying Ensembles: A General Certification Theory with S-Lipschitzness
63. ICML 2023Competitive Gradient Optimization
64. ICML 2023Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data
65. ICML 2023Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
66. ICML 2023DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization
67. ICML 2023Differentially Private Stochastic Convex Optimization under a Quantile Loss Function
68. ICML 2023Escaping saddle points in zeroth-order optimization: the power of two-point estimators
69. ICML 2023Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
70. ICML 2023Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
71. ICML 2023Faster Rates of Convergence to Stationary Points in Differentially Private Optimization
72. ICML 2023Generalized Polyak Step Size for First Order Optimization with Momentum
73. ICML 2023Global Optimization with Parametric Function Approximation
74. ICML 2023Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach
75. ICML 2023Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability
76. ICML 2023Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
77. ICML 2023Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization
78. ICML 2023Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods
79. ICML 2023Omnipredictors for Constrained Optimization
80. ICML 2023Optimization for Amortized Inverse Problems
81. ICML 2023PASTA: Pessimistic Assortment Optimization
82. ICML 2023Robustly Learning a Single Neuron via Sharpness
83. ICML 2023Second-Order Optimization with Lazy Hessians
84. ICML 2023Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function
85. ICML 2023Tilted Sparse Additive Models
86. ICML 2023Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization
87. NeurIPS 2023[Re] Bandit Theory and Thompson Sampling-guided Directed Evolution for Sequence Optimization
88. NeurIPS 2023A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
89. NeurIPS 2023A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
90. NeurIPS 2023Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization
91. NeurIPS 2023Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
92. NeurIPS 2023Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
93. NeurIPS 2023Advancing Bayesian Optimization via Learning Correlated Latent Space
94. NeurIPS 2023An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
95. NeurIPS 2023Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start
96. NeurIPS 2023Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control
97. NeurIPS 2023DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework
98. NeurIPS 2023Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
99. NeurIPS 2023Fast Partitioned Learned Bloom Filter
100. NeurIPS 2023Faster Margin Maximization Rates for Generic Optimization Methods

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.