Theory · optimization papers, 2023–2026
Theory area: optimization
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,871 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 37 | 46 | 35 | 5 | 123 |
| 2024 | 304 | 123 | 67 | 0 | 494 |
| 2025 | 318 | 196 | 147 | 9 | 670 |
| 2026 | 119 | 244 | 214 | 7 | 584 |
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
196 papers, page 3 of 4
- ICLR 2025Linear Partial Gromov-Wasserstein Embedding
- ICLR 2025LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch
- ICLR 2025Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold
- ICLR 2025Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation
- ICLR 2025Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression
- ICLR 2025LoCoDL: Communication-Efficient Distributed Learning with Local Training and Compression
- ICLR 2025LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
- ICLR 2025Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
- ICLR 2025Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
- ICLR 2025Making Transformer Decoders Better Differentiable Indexers
- ICLR 2025Mask in the Mirror: Implicit Sparsification
- ICLR 2025MAST: model-agnostic sparsified training
- ICLR 2025Matrix Product Sketching via Coordinated Sampling
- ICLR 2025Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity
- ICLR 2025Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
- ICLR 2025MGDA Converges under Generalized Smoothness, Provably
- ICLR 2025Minimalistic Predictions for Online Class Constraint Scheduling
- ICLR 2025MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
- ICLR 2025Multi-objective Differentiable Neural Architecture Search
- ICLR 2025Nesterov acceleration in benignly non-convex landscapes
- ICLR 2025Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization
- ICLR 2025New Algorithms for the Learning-Augmented k-means Problem
- ICLR 2025Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
- ICLR 2025Non-Equilibrium Dynamics of Hybrid Continuous-Discrete Ground-State Sampling
- ICLR 2025Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
- ICLR 2025Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
- ICLR 2025OCCAM: Towards Cost-Efficient and Accuracy-Aware Classification Inference
- ICLR 2025Offline Model-Based Optimization by Learning to Rank
- ICLR 2025On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime
- ICLR 2025On the Almost Sure Convergence of the Stochastic Three Points Algorithm
- ICLR 2025On the Crucial Role of Initialization for Matrix Factorization
- ICLR 2025On the Expressiveness of Rational ReLU Neural Networks With Bounded Depth
- ICLR 2025On the Optimal Memorization Capacity of Transformers
- ICLR 2025On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
- ICLR 2025On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
- ICLR 2025OPTAMI: Global Superlinear Convergence of High-order Methods
- ICLR 2025Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction
- ICLR 2025Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design
- ICLR 2025Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
- ICLR 2025Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
- ICLR 2025Optimizing Neural Network Representations of Boolean Networks
- ICLR 2025Oracle efficient truncated statistics
- ICLR 2025Overcoming Lower-Level Constraints in Bilevel Optimization: A Novel Approach with Regularized Gap Functions
- ICLR 2025Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization
- ICLR 2025Partial Gromov-Wasserstein Metric
- ICLR 2025Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
- ICLR 2025Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
- ICLR 2025Private Mechanism Design via Quantile Estimation
- ICLR 2025Probabilistic Neural Pruning via Sparsity Evolutionary Fokker-Planck-Kolmogorov Equation
- ICLR 2025Problem-Parameter-Free Federated Learning
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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.