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

346 papers, page 5 of 7

201. NeurIPS 2023A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization
202. NeurIPS 2023A Unified Framework for Rank-based Loss Minimization
203. NeurIPS 2023Accelerated Quasi-Newton Proximal Extragradient: Faster Rate for Smooth Convex Optimization
204. NeurIPS 2023Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance
205. NeurIPS 2023Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization
206. NeurIPS 2023Adaptive SGD with Polyak stepsize and Line-search: Robust Convergence and Variance Reduction
207. NeurIPS 2023Advancing Bayesian Optimization via Learning Correlated Latent Space
208. NeurIPS 2023An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
209. NeurIPS 2023An Exploration-by-Optimization Approach to Best of Both Worlds in Linear Bandits
210. NeurIPS 2023An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization
211. NeurIPS 2023An Optimization-based Approach To Node Role Discovery in Networks: Approximating Equitable Partitions
212. NeurIPS 2023AutoGO: Automated Computation Graph Optimization for Neural Network Evolution
213. NeurIPS 2023Batch Bayesian Optimization For Replicable Experimental Design
214. NeurIPS 2023Bias in Evaluation Processes: An Optimization-Based Model
215. NeurIPS 2023Bicriteria Approximation Algorithms for the Submodular Cover Problem
216. NeurIPS 2023Bilevel Optimization with a Lower-level Contraction: Optimal Sample Complexity without Warm-Start
217. NeurIPS 2023BiSLS/SPS: Auto-tune Step Sizes for Stable Bi-level Optimization
218. NeurIPS 2023Block Coordinate Plug-and-Play Methods for Blind Inverse Problems
219. NeurIPS 2023Boosting with Tempered Exponential Measures
220. NeurIPS 2023Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed Spaces
221. NeurIPS 2023Cascading Contextual Assortment Bandits
222. NeurIPS 2023Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
223. NeurIPS 2023Complexity of Derivative-Free Policy Optimization for Structured $\mathcal{H}_\infty$ Control
224. NeurIPS 2023Contextual Stochastic Bilevel Optimization
225. NeurIPS 2023Continuous-time Analysis of Anchor Acceleration
226. NeurIPS 2023Convergence of Adam Under Relaxed Assumptions
227. NeurIPS 2023Convergence of Alternating Gradient Descent for Matrix Factorization
228. NeurIPS 2023Convergence of mean-field Langevin dynamics: time-space discretization, stochastic gradient, and variance reduction
229. NeurIPS 2023Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems
230. NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
231. NeurIPS 2023CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
232. NeurIPS 2023Debiasing Conditional Stochastic Optimization
233. NeurIPS 2023Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence
234. NeurIPS 2023Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization
235. NeurIPS 2023Distributionally Robust Bayesian Optimization with $\varphi$-divergences
236. NeurIPS 2023Distributionally Robust Linear Quadratic Control
237. NeurIPS 2023Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models
238. NeurIPS 2023Don’t blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
239. NeurIPS 2023DRAUC: An Instance-wise Distributionally Robust AUC Optimization Framework
240. NeurIPS 2023DropCompute: simple and more robust distributed synchronous training via compute variance reduction
241. NeurIPS 2023Efficient Hyper-parameter Optimization with Cubic Regularization
242. NeurIPS 2023Efficient Robust Bayesian Optimization for Arbitrary Uncertain inputs
243. NeurIPS 2023Exponentially Convergent Algorithms for Supervised Matrix Factorization
244. NeurIPS 2023Failure-Aware Gaussian Process Optimization with Regret Bounds
245. NeurIPS 2023Fair Canonical Correlation Analysis
246. NeurIPS 2023FAMO: Fast Adaptive Multitask Optimization
247. NeurIPS 2023Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
248. NeurIPS 2023Fast Partitioned Learned Bloom Filter
249. NeurIPS 2023Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
250. NeurIPS 2023Faster Margin Maximization Rates for Generic Optimization Methods

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.