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 4 of 6

151. NeurIPS 2025MESS+: Dynamically Learned Inference-Time LLM Routing in Model Zoos with Service Level Guarantees
152. NeurIPS 2025Meta-Learning Objectives for Preference Optimization
153. NeurIPS 2025MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
154. NeurIPS 2025MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization
155. NeurIPS 2025MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
156. NeurIPS 2025Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling
157. NeurIPS 2025MOBO-OSD: Batch Multi-Objective Bayesian Optimization via Orthogonal Search Directions
158. NeurIPS 2025Momentum-SAM: Sharpness Aware Minimization without Computational Overhead
159. NeurIPS 2025Multi-Expert Distributionally Robust Optimization for Out-of-Distribution Generalization
160. NeurIPS 2025Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms
161. NeurIPS 2025Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
162. NeurIPS 2025Natural Gradient VI: Guarantees for Non-Conjugate Models
163. NeurIPS 2025Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference
164. NeurIPS 2025Neural Emulator Superiority: When Machine Learning for PDEs Surpasses its Training Data
165. NeurIPS 2025New Perspectives on the Polyak Stepsize: Surrogate Functions and Negative Results
166. NeurIPS 2025No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
167. NeurIPS 2025Non-convex entropic mean-field optimization via Best Response flow
168. NeurIPS 2025Non-Convex Tensor Recovery from Tube-Wise Sensing
169. NeurIPS 2025Non-monotone Submodular Optimization: $p$-Matchoid Constraints and Fully Dynamic Setting
170. NeurIPS 2025Non-Singularity of the Gradient Descent Map for Neural Networks with Piecewise Analytic Activations
171. NeurIPS 2025Non-stationary Bandit Convex Optimization: A Comprehensive Study
172. NeurIPS 2025Nonlinearly Preconditioned Gradient Methods: Momentum and Stochastic Analysis
173. NeurIPS 2025NopeRoomGS: Indoor 3D Gaussian Splatting Optimization without Camera Pose Input
174. NeurIPS 2025Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies
175. NeurIPS 2025Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
176. NeurIPS 2025OMiSO: Adaptive optimization of state-dependent brain stimulation to shape neural population states
177. NeurIPS 2025Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimization
178. NeurIPS 2025On Efficiency-Effectiveness Trade-off of Diffusion-based Recommenders
179. NeurIPS 2025On Extending Direct Preference Optimization to Accommodate Ties
180. NeurIPS 2025On the $O(\frac{\sqrt{d}}{K^{1/4}})$ Convergence Rate of AdamW Measured by $\ell_1$ Norm
181. NeurIPS 2025On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization
182. NeurIPS 2025On the Convergence of Single-Timescale Actor-Critic
183. NeurIPS 2025On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent
184. NeurIPS 2025On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
185. NeurIPS 2025On the Sample Complexity Bounds of Bilevel Reinforcement Learning
186. NeurIPS 2025On Traceability in $\ell_p$ Stochastic Convex Optimization
187. NeurIPS 2025Online Optimization for Offline Safe Reinforcement Learning
188. NeurIPS 2025Online Strategic Classification With Noise and Partial Feedback
189. NeurIPS 2025Optimistic Online-to-Batch Conversions for Accelerated Convergence and Universality
190. NeurIPS 2025PALQO: Physics-informed model for Accelerating Large-scale Quantum Optimization
191. NeurIPS 2025Partial Correlation Network Estimation by Semismooth Newton Methods
192. NeurIPS 2025Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
193. NeurIPS 2025PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs
194. NeurIPS 2025PDPO: Parametric Density Path Optimization
195. NeurIPS 2025Per-Architecture Training-Free Metric Optimization for Neural Architecture Search
196. NeurIPS 2025PhySense: Sensor Placement Optimization for Accurate Physics Sensing
197. NeurIPS 2025Preference Optimization by Estimating the Ratio of the Data Distribution
198. NeurIPS 2025Preference-Guided Diffusion for Multi-Objective Offline Optimization
199. NeurIPS 2025Preserving LLM Capabilities through Calibration Data Curation: From Analysis to Optimization
200. NeurIPS 2025PRESTO: Preimage-Informed Instruction Optimization for Prompting Black-Box LLMs

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.