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 11 of 13

501. ICLR 2024Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
502. ICLR 2024Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
503. ICLR 2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention
504. ICLR 2024Large Language Models to Enhance Bayesian Optimization
505. ICLR 2024Learning to Solve Bilevel Programs with Binary Tender
506. ICLR 2024Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning
507. ICLR 2024Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset
508. ICLR 2024Linear attention is (maybe) all you need (to understand Transformer optimization)
509. ICLR 2024Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts
510. ICLR 2024Local Composite Saddle Point Optimization
511. ICLR 2024LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models
512. ICLR 2024Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time
513. ICLR 2024Magnitude Invariant Parametrizations Improve Hypernetwork Learning
514. ICLR 2024Momentum Benefits Non-iid Federated Learning Simply and Provably
515. ICLR 2024Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss
516. ICLR 2024Near-Optimal Solutions of Constrained Learning Problems
517. ICLR 2024Neur2RO: Neural Two-Stage Robust Optimization
518. ICLR 2024New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions
519. ICLR 2024Noisy Interpolation Learning with Shallow Univariate ReLU Networks
520. ICLR 2024On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
521. ICLR 2024On the Effect of Batch Size in Byzantine-Robust Distributed Learning
522. ICLR 2024On the hardness of learning under symmetries
523. ICLR 2024On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback
524. ICLR 2024On the Parameterization of Second-Order Optimization Effective towards the Infinite Width
525. ICLR 2024On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks
526. ICLR 2024One Forward is Enough for Neural Network Training via Likelihood Ratio Method
527. ICLR 2024OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS
528. ICLR 2024Optimal Sample Complexity of Contrastive Learning
529. ICLR 2024Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms
530. ICLR 2024Optimistic Bayesian Optimization with Unknown Constraints
531. ICLR 2024Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization
532. ICLR 2024PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
533. ICLR 2024Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
534. ICLR 2024Private Zeroth-Order Nonsmooth Nonconvex Optimization
535. ICLR 2024Quadratic models for understanding catapult dynamics of neural networks
536. ICLR 2024Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
537. ICLR 2024Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
538. ICLR 2024Scaling Convex Neural Networks with Burer-Monteiro Factorization
539. ICLR 2024SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem
540. ICLR 2024Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity
541. ICLR 2024Small-scale proxies for large-scale Transformer training instabilities
542. ICLR 2024Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing
543. ICLR 2024Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
544. ICLR 2024Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming
545. ICLR 2024Stochastic Controlled Averaging for Federated Learning with Communication Compression
546. ICLR 2024SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
547. ICLR 2024Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems
548. ICLR 2024Symmetric Single Index Learning
549. ICLR 2024Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration
550. ICLR 2024Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks

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.