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 5 of 47

201. ICLR 2026Strongly Convex Sets in Riemannian Manifolds
202. ICLR 2026Submodular Function Minimization with Dueling Oracle
203. ICLR 2026SVD Provably Denoises Nearest Neighbor Data
204. ICLR 2026Symmetry-Aware Bayesian Optimization via Max Kernels
205. ICLR 2026Taming Score-Based Denoisers in ADMM: A Convergent Plug-and-Play Framework
206. ICLR 2026TAO-Attack: Toward Advanced Optimization-Based Jailbreak Attacks for Large Language Models
207. ICLR 2026Task-free Adaptive Meta Black-box Optimization
208. ICLR 2026The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton
209. ICLR 2026Token-Importance Guided Direct Preference Optimization
210. ICLR 2026Towards Dynamic Interleaving Optimizers
211. ICLR 2026Towards Learned Optimization Free Lunch
212. ICLR 2026Towards Real-World Routing with Neural Combinatorial Optimization
213. ICLR 2026Understanding and improving Shampoo and SOAP via Kullback-Leibler Minimization
214. ICLR 2026Uni-DPO: A Unified Paradigm for Dynamic Preference Optimization of LLMs
215. ICLR 2026Unified Analyses for Hierarchical Federated Learning: Topology Selection under Data Heterogeneity
216. ICLR 2026Unifying Formal Explanations: A Complexity-Theoretic Perspective
217. ICLR 2026Unifying Stable Optimization and Reference Regularization in RLHF
218. ICLR 2026Unlocking the Potential of Weighting Methods in Federated Learning Through Communication Compression
219. ICLR 2026Why DPO is a Misspecified Estimator and How to Fix It
220. ICLR 2026WILD-Diffusion: A WDRO Inspired Training Method for Diffusion Models under Limited Data
221. ICLR 2026XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning
222. ICML 2026$\alpha$-PFN: Fast Entropy Search via In-Context Learning
223. ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
224. ICML 2026$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
225. ICML 2026A Constrained Optimization Perspective of Unrolled Transformers
226. ICML 2026A Fully First-Order Layer for Differentiable Optimization
227. ICML 2026A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention
228. ICML 2026A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search
229. ICML 2026A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost
230. ICML 2026A proximal ADMM for multiblock problems with block anti-upper triangular constraints
231. ICML 2026A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms
232. ICML 2026A Solver-Free Training Method for Predict-then-Optimize
233. ICML 2026A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization
234. ICML 2026A Tight Theory of Error Feedback Algorithms in Distributed Optimization
235. ICML 2026Accelerated and Stable Convergence with Anchored Generalized Optimistic Method
236. ICML 2026Accelerated Dual Method for Distributed Optimization: An Inexact-Gradient View of Local Updates
237. ICML 2026Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization
238. ICML 2026Achieving Structurally Robust Gromov Wasserstein Distance via Adaptive Dual-Mask
239. ICML 2026Adapting to Evolving Graphs: A Scalable Framework for Dynamic Coarsening
240. ICML 2026Adaptive Momentum and Nonlinear Damping for Neural Network Training
241. ICML 2026Adaptive Sharpness-Aware Minimization with a Polyak-type Step size: A Theory-Grounded Scheduler
242. ICML 2026AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning
243. ICML 2026ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
244. ICML 2026All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension
245. ICML 2026AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training
246. ICML 2026An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale
247. ICML 2026An Exploration of Non-Euclidean Gradient Descent: Muon and its Many Variants
248. ICML 2026An Exterior Method for Nonnegative Matrix Factorization
249. ICML 2026ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization
250. ICML 2026Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization

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.