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

279 papers, page 5 of 6

201. NeurIPS 2025Probing Neural Combinatorial Optimization Models
202. NeurIPS 2025Problem-Parameter-Free Decentralized Bilevel Optimization
203. NeurIPS 2025ProfiX: Improving Profile-Guided Optimization in Compilers with Graph Neural Networks
204. NeurIPS 2025Proximalized Preference Optimization for Diverse Feedback Types: A Decomposed Perspective on DPO
205. NeurIPS 2025PseuZO: Pseudo-Zeroth-Order Algorithm for Training Deep Neural Networks
206. NeurIPS 2025Purifying Shampoo: Investigating Shampoo's Heuristics by Decomposing its Preconditioner
207. NeurIPS 2025Purity Law for Neural Routing Problem Solvers with Enhanced Generalizability
208. NeurIPS 2025Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning
209. NeurIPS 2025Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions
210. NeurIPS 2025Quantitative convergence of trained neural networks to Gaussian processes
211. NeurIPS 2025Quantum Speedups for Minimax Optimization and Beyond
212. NeurIPS 2025Quasi-Self-Concordant Optimization with $\ell_{\infty}$ Lewis Weights
213. NeurIPS 2025ReDit: Reward Dithering for Improved LLM Policy Optimization
214. NeurIPS 2025RefLoRA: Refactored Low-Rank Adaptation for Efficient Fine-Tuning of Large Models
215. NeurIPS 2025RePO: Understanding Preference Learning Through ReLU-Based Optimization
216. NeurIPS 2025Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
217. NeurIPS 2025Rethinking PCA Through Duality
218. NeurIPS 2025Revisiting Consensus Error: A Fine-grained Analysis of Local SGD under Second-order Data Heterogeneity
219. NeurIPS 2025Revisiting Frank-Wolfe for Structured Nonconvex Optimization
220. NeurIPS 2025Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions
221. NeurIPS 2025RGB-Only Supervised Camera Parameter Optimization in Dynamic Scenes
222. NeurIPS 2025Risk-aware Direct Preference Optimization under Nested Risk Measure
223. NeurIPS 2025Robust Federated Finetuning of LLMs via Alternating Optimization of LoRA
224. NeurIPS 2025Robust Hyperbolic Learning with Curvature-Aware Optimization
225. NeurIPS 2025Robust LLM Alignment via Distributionally Robust Direct Preference Optimization
226. NeurIPS 2025RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Models
227. NeurIPS 2025RoPECraft: Training-Free Motion Transfer with Trajectory-Guided RoPE Optimization on Diffusion Transformers
228. NeurIPS 2025SAD Neural Networks: Divergent Gradient Flows and Asymptotic Optimality via o-minimal Structures
229. NeurIPS 2025Scalable inference of functional neural connectivity at submillisecond timescales
230. NeurIPS 2025Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf’s Law
231. NeurIPS 2025SDPGO: Efficient Self-Distillation Training Meets Proximal Gradient Optimization
232. NeurIPS 2025Second-Order Convergence in Private Stochastic Non-Convex Optimization
233. NeurIPS 2025Second-order Optimization under Heavy-Tailed Noise: Hessian Clipping and Sample Complexity Limits
234. NeurIPS 2025Segment Policy Optimization: Effective Segment-Level Credit Assignment in RL for Large Language Models
235. NeurIPS 2025Semi-infinite Nonconvex Constrained Min-Max Optimization
236. NeurIPS 2025Set Smoothness Unlocks Clarke Hyper-stationarity in Bilevel Optimization
237. NeurIPS 2025Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings
238. NeurIPS 2025Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning
239. NeurIPS 2025Sketched Adaptive Distributed Deep Learning: A Sharp Convergence Analysis
240. NeurIPS 2025Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraints
241. NeurIPS 2025Solver-Free Decision-Focused Learning for Linear Optimization Problems
242. NeurIPS 2025Solving Neural Min-Max Games: The Role of Architecture, Initialization & Dynamics
243. NeurIPS 2025Solving the Asymmetric Traveling Salesman Problem via Trace-Guided Cost Augmentation
244. NeurIPS 2025Spike-timing-dependent Hebbian learning as noisy gradient descent
245. NeurIPS 2025SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes
246. NeurIPS 2025Stab-SGD: Noise-Adaptivity in Smooth Optimization with Stability Ratios
247. NeurIPS 2025Stability and Sharper Risk Bounds with Convergence Rate $\tilde{O}(1/n^2)$
248. NeurIPS 2025Stable Coresets via Posterior Sampling: Aligning Induced and Full Loss Landscapes
249. NeurIPS 2025Stepsize anything: A unified learning rate schedule for budgeted-iteration training
250. NeurIPS 2025Stochastic Gradients under Nuisances

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.