Nonconvex Optimization papers, 2023–2026

Key findings

• Nonconvex Optimization went from 346 papers in 2023 to 757 in 2026, roughly 2.2x in three years.
• NeurIPS publishes the most Nonconvex Optimization work: 958 papers from 2023 to 2026, 41% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 2 in 2023 to 44 in 2026.
• Among the 5 topics under Optimization and Scaling, it ranks #2 by 2026 paper count; the fastest grower in the group, Scaling Laws, is up 4.1x versus 2.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026$\gamma$-weakly $\theta$-up-concavity: A Unified Framework for Non-Convex Optimization Beyond DR-Submodular and OSS Functions
• ICML 2026$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
• ICLR 2026Behavioral Embeddings of Programs: A Quasi-Dynamic Approach for Optimization Prediction
• CVPR 2026Coverage Optimization for Camera View Selection
• NeurIPS 2025Beyond Random: Automatic Inner-loop Optimization in Dataset Distillation
• ICML 2025A Bregman Proximal Viewpoint on Neural Operators
• ICLR 2025A Truncated Newton Method for Optimal Transport
• CVPR 2025Balanced Rate-Distortion Optimization in Learned Image Compression
• NeurIPS 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences
• ICML 2024A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
• ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
• CVPR 2024FaceCom: Towards High-fidelity 3D Facial Shape Completion via Optimization and Inpainting Guidance
• NeurIPS 2023A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting
• ICML 2023A Distribution Optimization Framework for Confidence Bounds of Risk Measures
• ICLR 2023A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta.
• CVPR 2023Attribute-Preserving Face Dataset Anonymization via Latent Code Optimization
• NeurIPS 2026A Doubly Smoothed Decentralized Stochastic Minimax Optimization Algorithm
• ICML 2026A Constrained Optimization Perspective of Unrolled Transformers
• ICLR 2026BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
• CVPR 2026Fully Decentralized Certified Unlearning

All Nonconvex Optimization papers

2,330 papers, page 46 of 47

2251. NeurIPS 2023Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization
2252. NeurIPS 2023Knowledge Distillation Performs Partial Variance Reduction
2253. NeurIPS 2023L2T-DLN: Learning to Teach with Dynamic Loss Network
2254. NeurIPS 2023Learning Cuts via Enumeration Oracles
2255. NeurIPS 2023Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt
2256. NeurIPS 2023Leveraging the two-timescale regime to demonstrate convergence of neural networks
2257. NeurIPS 2023Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices
2258. NeurIPS 2023Max-Margin Token Selection in Attention Mechanism
2259. NeurIPS 2023Mechanic: A Learning Rate Tuner
2260. NeurIPS 2023Memory-Constrained Algorithms for Convex Optimization
2261. NeurIPS 2023MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning
2262. NeurIPS 2023MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
2263. NeurIPS 2023Model-Based Control with Sparse Neural Dynamics
2264. NeurIPS 2023Momentum Provably Improves Error Feedback!
2265. NeurIPS 2023Neural Fields with Hard Constraints of Arbitrary Differential Order
2266. NeurIPS 2023Non-Convex Bilevel Optimization with Time-Varying Objective Functions
2267. NeurIPS 2023Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization
2268. NeurIPS 2023On skip connections and normalisation layers in deep optimisation
2269. NeurIPS 2023On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis
2270. NeurIPS 2023On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
2271. NeurIPS 2023On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
2272. NeurIPS 2023One-step differentiation of iterative algorithms
2273. NeurIPS 2023Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure
2274. NeurIPS 2023Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
2275. NeurIPS 2023Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model
2276. NeurIPS 2023Optimization of Inter-group criteria for clustering with minimum size constraints
2277. NeurIPS 2023Oracle Complexity of Single-Loop Switching Subgradient Methods for Non-Smooth Weakly Convex Functional Constrained Optimization
2278. NeurIPS 2023Ordering-based Conditions for Global Convergence of Policy Gradient Methods
2279. NeurIPS 2023Outlier-Robust Gromov-Wasserstein for Graph Data
2280. NeurIPS 2023Outlier-Robust Wasserstein DRO
2281. NeurIPS 2023Parallel Submodular Function Minimization
2282. NeurIPS 2023Parallel-mentoring for Offline Model-based Optimization
2283. NeurIPS 2023Physics-Informed Bayesian Optimization of Variational Quantum Circuits
2284. NeurIPS 2023Policy Optimization for Continuous Reinforcement Learning
2285. NeurIPS 2023Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima
2286. NeurIPS 2023Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
2287. NeurIPS 2023PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
2288. NeurIPS 2023Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks
2289. NeurIPS 2023Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems
2290. NeurIPS 2023Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem
2291. NeurIPS 2023PROTES: Probabilistic Optimization with Tensor Sampling
2292. NeurIPS 2023Provable convergence guarantees for black-box variational inference
2293. NeurIPS 2023Quantum Bayesian Optimization
2294. NeurIPS 2023Quantum speedups for stochastic optimization
2295. NeurIPS 2023Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization
2296. NeurIPS 2023Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
2297. NeurIPS 2023Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
2298. NeurIPS 2023ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
2299. NeurIPS 2023Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?
2300. NeurIPS 2023Riemannian Projection-free Online Learning

FAQ

How many Nonconvex Optimization papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,330 in total: 346 in 2023, 560 in 2024, 667 in 2025, 757 in 2026.

How many Nonconvex Optimization papers are at NeurIPS 2026?

NeurIPS 2026 has 250 Nonconvex Optimization papers, versus 279 the year before.

How many Nonconvex Optimization papers are at ICLR 2026?

ICLR 2026 has 178 Nonconvex Optimization papers, versus 177 the year before.

How many Nonconvex Optimization papers are at ICML 2026?

ICML 2026 has 286 Nonconvex Optimization papers, versus 192 the year before.

How many Nonconvex Optimization papers are at CVPR 2026?

CVPR 2026 has 43 Nonconvex Optimization papers, versus 19 the year before.

Which conference publishes the most Nonconvex Optimization papers?

NeurIPS, with 958 papers from 2023 to 2026.