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 34 of 38

1651. NeurIPS 2024OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation
1652. NeurIPS 2024Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport
1653. NeurIPS 2024Overcoming Brittleness in Pareto-Optimal Learning Augmented Algorithms
1654. NeurIPS 2024PAC-Bayes-Chernoff bounds for unbounded losses
1655. NeurIPS 2024Parameter-free Clipped Gradient Descent Meets Polyak
1656. NeurIPS 2024Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds
1657. NeurIPS 2024Performative Control for Linear Dynamical Systems
1658. NeurIPS 2024Practical $0.385$-Approximation for Submodular Maximization Subject to a Cardinality Constraint
1659. NeurIPS 2024Pre-trained Gaussian Processes for Bayesian Optimization
1660. NeurIPS 2024Pretrained Optimization Model for Zero-Shot Black Box Optimization
1661. NeurIPS 2024Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry
1662. NeurIPS 2024Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions
1663. NeurIPS 2024Prospective Learning: Learning for a Dynamic Future
1664. NeurIPS 2024Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
1665. NeurIPS 2024Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
1666. NeurIPS 2024Quantitative Convergences of Lie Group Momentum Optimizers
1667. NeurIPS 2024Quantum Algorithms for Non-smooth Non-convex Optimization
1668. NeurIPS 2024Query-Efficient Correlation Clustering with Noisy Oracle
1669. NeurIPS 2024Random Function Descent
1670. NeurIPS 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
1671. NeurIPS 2024Rejection via Learning Density Ratios
1672. NeurIPS 2024Reliable Learning of Halfspaces under Gaussian Marginals
1673. NeurIPS 2024ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
1674. NeurIPS 2024Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
1675. NeurIPS 2024Replicable Uniformity Testing
1676. NeurIPS 2024Rethinking 3D Convolution in $\ell_p$-norm Space
1677. NeurIPS 2024Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
1678. NeurIPS 2024Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications
1679. NeurIPS 2024S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization
1680. NeurIPS 2024Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
1681. NeurIPS 2024Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut
1682. NeurIPS 2024Sample-Efficient Agnostic Boosting
1683. NeurIPS 2024Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
1684. NeurIPS 2024Scalable Kernel Inverse Optimization
1685. NeurIPS 2024Scalable Optimization in the Modular Norm
1686. NeurIPS 2024Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting
1687. NeurIPS 2024Semidefinite Relaxations of the Gromov-Wasserstein Distance
1688. NeurIPS 2024SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
1689. NeurIPS 2024Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
1690. NeurIPS 2024Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
1691. NeurIPS 2024Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
1692. NeurIPS 2024Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
1693. NeurIPS 2024SkipPredict: When to Invest in Predictions for Scheduling
1694. NeurIPS 2024Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover
1695. NeurIPS 2024SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
1696. NeurIPS 2024Solving Sparse \& High-Dimensional-Output Regression via Compression
1697. NeurIPS 2024SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
1698. NeurIPS 2024Stabilized Proximal-Point Methods for Federated Optimization
1699. NeurIPS 2024Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes
1700. NeurIPS 2024Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm

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.