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

670 papers, page 7 of 14

301. ICML 2025On the Local Complexity of Linear Regions in Deep ReLU Networks
302. ICML 2025Online Conformal Prediction via Online Optimization
303. ICML 2025Optimal Decision Tree Pruning Revisited: Algorithms and Complexity
304. ICML 2025Optimization for Neural Operators can Benefit from Width
305. ICML 2025Optimization over Sparse Support-Preserving Sets: Two-Step Projection with Global Optimality Guarantees
306. ICML 2025OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling
307. ICML 2025PARQ: Piecewise-Affine Regularized Quantization
308. ICML 2025PDUDT: Provable Decentralized Unlearning under Dynamic Topologies
309. ICML 2025Policy Optimization for CMDPs with Bandit Feedback: Learning Stochastic and Adversarial Constraints
310. ICML 2025Polynomial Time Learning Augmented Algorithms for NP-hard Permutation Problems
311. ICML 2025Position: A Theory of Deep Learning Must Include Compositional Sparsity
312. ICML 2025Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
313. ICML 2025Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
314. ICML 2025Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All
315. ICML 2025Principled Algorithms for Optimizing Generalized Metrics in Binary Classification
316. ICML 2025Procurement Auctions via Approximately Optimal Submodular Optimization
317. ICML 2025Radio: Rate–Distortion Optimization for Large Language Model Compression
318. ICML 2025Rapid Overfitting of Multi-Pass SGD in Stochastic Convex Optimization
319. ICML 2025Reducing Variance of Stochastic Optimization for Approximating Nash Equilibria in Normal-Form Games
320. ICML 2025Retraining with Predicted Hard Labels Provably Increases Model Accuracy
321. ICML 2025Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness
322. ICML 2025Robust Sparsification via Sensitivity
323. ICML 2025ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
324. ICML 2025Safe-EF: Error Feedback for Non-smooth Constrained Optimization
325. ICML 2025Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up
326. ICML 2025Scalable Meta-Learning via Mixed-Mode Differentiation
327. ICML 2025Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
328. ICML 2025Schwarz–Schur Involution: Lightspeed Differentiable Sparse Linear Solvers
329. ICML 2025SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
330. ICML 2025SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
331. ICML 2025SERENA: A Unified Stochastic Recursive Variance Reduced Gradient Framework for Riemannian Non-Convex Optimization
332. ICML 2025Sharp Optimality of Simple, Plug-in Estimation of the Fisher Information of a Smoothed Density
333. ICML 2025Simplicity Bias and Optimization Threshold in Two-Layer ReLU Networks
334. ICML 2025Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry
335. ICML 2025Sparse-pivot: Dynamic correlation clustering for node insertions
336. ICML 2025SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models
337. ICML 2025Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization
338. ICML 2025Stochastic Deep Restoration Priors for Imaging Inverse Problems
339. ICML 2025Structured Preconditioners in Adaptive Optimization: A Unified Analysis
340. ICML 2025Subspace Optimization for Large Language Models with Convergence Guarantees
341. ICML 2025The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
342. ICML 2025The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
343. ICML 2025The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations
344. ICML 2025The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training
345. ICML 2025Tilted Sharpness-Aware Minimization
346. ICML 2025Toward a Unified Theory of Gradient Descent under Generalized Smoothness
347. ICML 2025Towards a Formal Theory of Representational Compositionality
348. ICML 2025Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
349. ICML 2025Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
350. ICML 2025TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel 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.