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

736 papers, page 5 of 15

201. ICML 2026Parallel Stochastic Gradient-Based Planning for World Models
202. ICML 2026Parameter-Masked Decoupled Optimization for Cross-Domain Class-Incremental Learning
203. ICML 2026PASO: Step Parallel Stochastic Optimization
204. ICML 2026PepCompass: Navigating Peptide Embedding Spaces Using Riemannian Geometry
205. ICML 2026PICACO: Pluralistic In-Context Value Alignment via Total Correlation Optimization
206. ICML 2026Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes
207. ICML 2026Preconditioning Neural Tangent Kernel for Adaptive Optimization
208. ICML 2026Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction
209. ICML 2026Preference-Modulated Structural Attention for Multi-Objective Combinatorial Optimization
210. ICML 2026Probability of Matching for Batch Multi-Objective Bayesian Optimization
211. ICML 2026Projection-Free Algorithms for Minimax Problems
212. ICML 2026QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning
213. ICML 2026Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes
214. ICML 2026Ratio-Variance Regularized Policy Optimization
215. ICML 2026Recursive Monte-Carlo Tree Search
216. ICML 2026Reducing Per-Sample Harm in Stochastic Optimization
217. ICML 2026Reflect-then-Correct: Rebalancing Task Optimization for Generalizable Meta-Reinforcement Learning via Distributional Value Error Reduction
218. ICML 2026Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
219. ICML 2026Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief
220. ICML 2026Reparameterization Flow Policy Optimization
221. ICML 2026Reparameterization Proximal Policy Optimization
222. ICML 2026Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models
223. ICML 2026Rethinking Convergence in MoE Training: The Role of Routing Sparsity
224. ICML 2026Rethinking Neural Network Learning Rates: A Stackelberg Perspective
225. ICML 2026Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games
226. ICML 2026Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens
227. ICML 2026Riemannian Dueling Optimization
228. ICML 2026Riemannian Optimization for Fair Spectral Clustering
229. ICML 2026Riemannian stochastic optimization for sufficient dimension reduction
230. ICML 2026RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
231. ICML 2026Robust Bayesian Optimisation with Unbounded Corruptions
232. ICML 2026Robust Contextual Optimization with Missing Covariates
233. ICML 2026Robust Learning via Nested Distributionally Robust Optimization
234. ICML 2026Romberg-Extrapolated Zeroth-Order Gradient Estimator: Higher-Order Bias Reduction with Preserved Leading Directional Variance
235. ICML 2026Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
236. ICML 2026SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling
237. ICML 2026Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients
238. ICML 2026SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference
239. ICML 2026Scalable and Stable Estimation of Amari $\alpha$-Divergence using Random Fourier Features
240. ICML 2026Second-Order Bilevel Optimization with Accelerated Convergence Rates
241. ICML 2026Segment-Aligned Policy Optimization for Multi-Modal Reasoning
242. ICML 2026Sharpness-Aware Minimization Can Hallucinate Minimizers
243. ICML 2026SimpleGPT: Improving GPT via A Simple Normalization Strategy
244. ICML 2026Simultaneous Confidence Bounds for Aggregated Effects via Exact Subset Optimization
245. ICML 2026Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization
246. ICML 2026SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
247. ICML 2026Softsign: Smooth Sign in Your Optimizer For Better Parameter Heterogeneity Handling
248. ICML 2026Solving Imperfect-Recall Games via Sum-of-Squares Optimization
249. ICML 2026Solving Stochastic Variational Inequalities without the Bounded Variance Assumption
250. ICML 2026Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel 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.