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 14 of 16

651. NeurIPS 2024Practical $0.385$-Approximation for Submodular Maximization Subject to a Cardinality Constraint
652. NeurIPS 2024Pre-trained Gaussian Processes for Bayesian Optimization
653. NeurIPS 2024Pretrained Optimization Model for Zero-Shot Black Box Optimization
654. NeurIPS 2024Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
655. NeurIPS 2024Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions
656. NeurIPS 2024Prospective Learning: Learning for a Dynamic Future
657. NeurIPS 2024Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
658. NeurIPS 2024Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
659. NeurIPS 2024Quantitative Convergences of Lie Group Momentum Optimizers
660. NeurIPS 2024Quantum Algorithms for Non-smooth Non-convex Optimization
661. NeurIPS 2024Query-Efficient Correlation Clustering with Noisy Oracle
662. NeurIPS 2024Random Function Descent
663. NeurIPS 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
664. NeurIPS 2024Rejection via Learning Density Ratios
665. NeurIPS 2024Reliable Learning of Halfspaces under Gaussian Marginals
666. NeurIPS 2024ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
667. NeurIPS 2024Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
668. NeurIPS 2024Replicable Uniformity Testing
669. NeurIPS 2024Rethinking 3D Convolution in $\ell_p$-norm Space
670. NeurIPS 2024Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
671. NeurIPS 2024Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications
672. NeurIPS 2024S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization
673. NeurIPS 2024Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
674. NeurIPS 2024Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut
675. NeurIPS 2024Sample-Efficient Agnostic Boosting
676. NeurIPS 2024Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
677. NeurIPS 2024Scalable Kernel Inverse Optimization
678. NeurIPS 2024Scalable Optimization in the Modular Norm
679. NeurIPS 2024Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
680. NeurIPS 2024Semidefinite Relaxations of the Gromov-Wasserstein Distance
681. NeurIPS 2024SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
682. NeurIPS 2024Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
683. NeurIPS 2024Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
684. NeurIPS 2024Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
685. NeurIPS 2024Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
686. NeurIPS 2024SkipPredict: When to Invest in Predictions for Scheduling
687. NeurIPS 2024Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover
688. NeurIPS 2024SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
689. NeurIPS 2024Solving Sparse \& High-Dimensional-Output Regression via Compression
690. NeurIPS 2024SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
691. NeurIPS 2024Stabilized Proximal-Point Methods for Federated Optimization
692. NeurIPS 2024Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes
693. NeurIPS 2024Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
694. NeurIPS 2024Stepwise Alignment for Constrained Language Model Policy Optimization
695. NeurIPS 2024Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
696. NeurIPS 2024Stochastic Newton Proximal Extragradient Method
697. NeurIPS 2024Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
698. NeurIPS 2024Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
699. NeurIPS 2024Super Consistency of Neural Network Landscapes and Learning Rate Transfer
700. NeurIPS 2024SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization

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.