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 45 of 47

2201. NeurIPS 2023BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization
2202. NeurIPS 2023Block Coordinate Plug-and-Play Methods for Blind Inverse Problems
2203. NeurIPS 2023Boosting with Tempered Exponential Measures
2204. NeurIPS 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
2205. NeurIPS 2023Cascading Contextual Assortment Bandits
2206. NeurIPS 2023Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
2207. NeurIPS 2023Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control
2208. NeurIPS 2023Contextual Stochastic Bilevel Optimization
2209. NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
2210. NeurIPS 2023Convergence of Adam Under Relaxed Assumptions
2211. NeurIPS 2023Convergence of Alternating Gradient Descent for Matrix Factorization
2212. NeurIPS 2023Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
2213. NeurIPS 2023Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems
2214. NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
2215. NeurIPS 2023CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
2216. NeurIPS 2023Debiasing Conditional Stochastic Optimization
2217. NeurIPS 2023Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence
2218. NeurIPS 2023Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization
2219. NeurIPS 2023Distributionally Robust Bayesian Optimization with $\varphi$-divergences
2220. NeurIPS 2023Distributionally Robust Linear Quadratic Control
2221. NeurIPS 2023Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models
2222. NeurIPS 2023Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
2223. NeurIPS 2023DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework
2224. NeurIPS 2023DropCompute: simple and more robust distributed synchronous training via compute variance reduction
2225. NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
2226. NeurIPS 2023Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs
2227. NeurIPS 2023Exponentially Convergent Algorithms for Supervised Matrix Factorization
2228. NeurIPS 2023Failure-Aware Gaussian Process Optimization with Regret Bounds
2229. NeurIPS 2023Fair Canonical Correlation Analysis
2230. NeurIPS 2023FAMO: Fast Adaptive Multitask Optimization
2231. NeurIPS 2023Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
2232. NeurIPS 2023Fast Partitioned Learned Bloom Filter
2233. NeurIPS 2023Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
2234. NeurIPS 2023Faster Margin Maximization Rates for Generic Optimization Methods
2235. NeurIPS 2023Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
2236. NeurIPS 2023Federated Conditional Stochastic Optimization
2237. NeurIPS 2023Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
2238. NeurIPS 2023FedNAR: Federated Optimization with Normalized Annealing Regularization
2239. NeurIPS 2023Finding Local Minima Efficiently in Decentralized Optimization
2240. NeurIPS 2023Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization
2241. NeurIPS 2023First Order Stochastic Optimization with Oblivious Noise
2242. NeurIPS 2023Fractal Landscapes in Policy Optimization
2243. NeurIPS 2023Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization
2244. NeurIPS 2023Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization
2245. NeurIPS 2023Global Identifiability of $\ell_1$-based Dictionary Learning via Matrix Volume Optimization
2246. NeurIPS 2023GloptiNets: Scalable Non-Convex Optimization with Certificates
2247. NeurIPS 2023Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity
2248. NeurIPS 2023Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures
2249. NeurIPS 2023Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise
2250. NeurIPS 2023Improving the Knowledge Gradient Algorithm

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.