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 33 of 38

1601. NeurIPS 2024MAC Advice for facility location mechanism design
1602. NeurIPS 2024Matching the Statistical Query Lower Bound for $k$-Sparse Parity Problems with Sign Stochastic Gradient Descent
1603. NeurIPS 2024Mean-Field Langevin Dynamics for Signed Measures via a Bilevel Approach
1604. NeurIPS 2024Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
1605. NeurIPS 2024Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization
1606. NeurIPS 2024Mirror and Preconditioned Gradient Descent in Wasserstein Space
1607. NeurIPS 2024Monte Carlo Tree Search based Space Transfer for Black Box Optimization
1608. NeurIPS 2024Motif-oriented influence maximization for viral marketing in large-scale social networks
1609. NeurIPS 2024Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs
1610. NeurIPS 2024Multi-turn Reinforcement Learning with Preference Human Feedback
1611. NeurIPS 2024Multidimensional Fractional Programming for Normalized Cuts
1612. NeurIPS 2024MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encoding
1613. NeurIPS 2024Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity
1614. NeurIPS 2024Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD
1615. NeurIPS 2024Near-Optimality of Contrastive Divergence Algorithms
1616. NeurIPS 2024Nesterov acceleration despite very noisy gradients
1617. NeurIPS 2024Neur2BiLO: Neural Bilevel Optimization
1618. NeurIPS 2024Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation
1619. NeurIPS 2024Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits
1620. NeurIPS 2024Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search
1621. NeurIPS 2024Non-geodesically-convex optimization in the Wasserstein space
1622. NeurIPS 2024Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
1623. NeurIPS 2024Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
1624. NeurIPS 2024Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers
1625. NeurIPS 2024Nuclear Norm Regularization for Deep Learning
1626. NeurIPS 2024Oja's Algorithm for Streaming Sparse PCA
1627. NeurIPS 2024On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
1628. NeurIPS 2024On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
1629. NeurIPS 2024On Sparse Canonical Correlation Analysis
1630. NeurIPS 2024On the cohesion and separability of average-link for hierarchical agglomerative clustering
1631. NeurIPS 2024On the Comparison between Multi-modal and Single-modal Contrastive Learning
1632. NeurIPS 2024On the Computational Landscape of Replicable Learning
1633. NeurIPS 2024On the Efficiency of ERM in Feature Learning
1634. NeurIPS 2024On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
1635. NeurIPS 2024On the Limitations of Fractal Dimension as a Measure of Generalization
1636. NeurIPS 2024On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization
1637. NeurIPS 2024On the Sparsity of the Strong Lottery Ticket Hypothesis
1638. NeurIPS 2024On the Stability and Generalization of Meta-Learning
1639. NeurIPS 2024On Tractable $\Phi$-Equilibria in Non-Concave Games
1640. NeurIPS 2024OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
1641. NeurIPS 2024Optimal Algorithms for Augmented Testing of Discrete Distributions
1642. NeurIPS 2024Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
1643. NeurIPS 2024Optimal and Approximate Adaptive Stochastic Quantization
1644. NeurIPS 2024Optimal Classification under Performative Distribution Shift
1645. NeurIPS 2024Optimal Parallelization of Boosting
1646. NeurIPS 2024Optimal Scalarizations for Sublinear Hypervolume Regret
1647. NeurIPS 2024Optimization Algorithm Design via Electric Circuits
1648. NeurIPS 2024Optimization Can Learn Johnson Lindenstrauss Embeddings
1649. NeurIPS 2024Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition
1650. NeurIPS 2024Ordered Momentum for Asynchronous SGD

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.