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 25 of 38

1201. NeurIPS 2025Smoothed Agnostic Learning of Halfspaces over the Hypercube
1202. NeurIPS 2025Solver-Free Decision-Focused Learning for Linear Optimization Problems
1203. NeurIPS 2025Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling
1204. NeurIPS 2025Solving Neural Min-Max Games: The Role of Architecture, Initialization & Dynamics
1205. NeurIPS 2025Solving the Asymmetric Traveling Salesman Problem via Trace-Guided Cost Augmentation
1206. NeurIPS 2025Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning
1207. NeurIPS 2025Sparse Polyak: an adaptive step size rule for high-dimensional M-estimation
1208. NeurIPS 2025Spectral Estimation with Free Decompression
1209. NeurIPS 2025Stab-SGD: Noise-Adaptivity in Smooth Optimization with Stability Ratios
1210. NeurIPS 2025Stable Coresets via Posterior Sampling: Aligning Induced and Full Loss Landscapes
1211. NeurIPS 2025Stochastic Gradients under Nuisances
1212. NeurIPS 2025Stochastic Momentum Methods for Non-smooth Non-Convex Finite-Sum Coupled Compositional Optimization
1213. NeurIPS 2025Stochastic Optimization in Semi-Discrete Optimal Transport: Convergence Analysis and Minimax Rate
1214. NeurIPS 2025Streaming Attention Approximation via Discrepancy Theory
1215. NeurIPS 2025Streaming Federated Learning with Markovian Data
1216. NeurIPS 2025Streaming Stochastic Submodular Maximization with On-Demand User Requests
1217. NeurIPS 2025System Prompt Optimization with Meta-Learning
1218. NeurIPS 2025Targeted Maximum Likelihood Learning: An Optimization Perspective
1219. NeurIPS 2025The Bias-Variance Tradeoff in Data-Driven Optimization: A Local Misspecification Perspective
1220. NeurIPS 2025The Complexity of Finding Local Optima in Contrastive Learning
1221. NeurIPS 2025The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games
1222. NeurIPS 2025The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
1223. NeurIPS 2025The Flood Complex: Large-Scale Persistent Homology on Millions of Points
1224. NeurIPS 2025The Nuclear Route: Sharp Asymptotics of ERM in Overparameterized Quadratic Networks
1225. NeurIPS 2025The Persistence of Neural Collapse Despite Low-Rank Bias
1226. NeurIPS 2025The Rich and the Simple: On the Implicit Bias of Adam and SGD
1227. NeurIPS 2025Theoretical Investigation of Adafactor for Non-Convex Smooth Optimization
1228. NeurIPS 2025Tight analyses of first-order methods with error feedback
1229. NeurIPS 2025Tight Asymptotics of Extreme Order Statistics
1230. NeurIPS 2025Tight High-Probability Bounds for Nonconvex Heavy-Tailed Scenario under Weaker Assumptions
1231. NeurIPS 2025Tight Lower Bounds and Improved Convergence in Performative Prediction
1232. NeurIPS 2025Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling
1233. NeurIPS 2025Towards Straggler-Resilient Split Federated Learning: An Unbalanced Update Approach
1234. NeurIPS 2025Tractable Multinomial Logit Contextual Bandits with Non-Linear Utilities
1235. NeurIPS 2025Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization
1236. NeurIPS 2025TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks
1237. NeurIPS 2025Two Heads are Better than One: Simulating Large Transformers with Small Ones
1238. NeurIPS 2025UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection
1239. NeurIPS 2025Unbalanced Optimal Total Variation Transport: A Theoretical Approach to Spatial Resource Allocation Problems
1240. NeurIPS 2025Uncoupled and Convergent Learning in Monotone Games under Bandit Feedback
1241. NeurIPS 2025Understanding Data Influence in Reinforcement Finetuning
1242. NeurIPS 2025Understanding outer learning rates in Local SGD
1243. NeurIPS 2025Understanding Softmax Attention Layers:\\ Exact Mean-Field Analysis on a Toy Problem
1244. NeurIPS 2025Uniform Wrappers: Bridging Concave to Quadratizable Functions in Online Optimization
1245. NeurIPS 2025UniteFormer: Unifying Node and Edge Modalities in Transformers for Vehicle Routing Problems
1246. NeurIPS 2025Unlocking Dataset Distillation with Diffusion Models
1247. NeurIPS 2025Unveiling m-Sharpness Through the Structure of Stochastic Gradient Noise
1248. NeurIPS 2025What Data Enables Optimal Decisions? An Exact Characterization for Linear Optimization
1249. NeurIPS 2025What Expressivity Theory Misses: Message Passing Complexity for GNNs
1250. NeurIPS 2025What Makes a Reward Model a Good Teacher? An Optimization Perspective

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.