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

275 papers, page 5 of 6

201. NeurIPS 2024Rejection via Learning Density Ratios
202. NeurIPS 2024ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
203. NeurIPS 2024Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
204. NeurIPS 2024Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
205. NeurIPS 2024Resolving Discrepancies in Compute-Optimal Scaling of Language Models
206. NeurIPS 2024Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
207. NeurIPS 2024Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
208. NeurIPS 2024Robust Gaussian Processes via Relevance Pursuit
209. NeurIPS 2024Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
210. NeurIPS 2024S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization
211. NeurIPS 2024Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
212. NeurIPS 2024Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
213. NeurIPS 2024Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
214. NeurIPS 2024Scalable Kernel Inverse Optimization
215. NeurIPS 2024Scalable Optimization in the Modular Norm
216. NeurIPS 2024Second-order forward-mode optimization of recurrent neural networks for neuroscience
217. NeurIPS 2024Semidefinite Relaxations of the Gromov-Wasserstein Distance
218. NeurIPS 2024SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
219. NeurIPS 2024Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
220. NeurIPS 2024Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization
221. NeurIPS 2024Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
222. NeurIPS 2024Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
223. NeurIPS 2024Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
224. NeurIPS 2024Sketching for Distributed Deep Learning: A Sharper Analysis
225. NeurIPS 2024SkipPredict: When to Invest in Predictions for Scheduling
226. NeurIPS 2024SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
227. NeurIPS 2024SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
228. NeurIPS 2024Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation
229. NeurIPS 2024Stabilized Proximal-Point Methods for Federated Optimization
230. NeurIPS 2024Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
231. NeurIPS 2024Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
232. NeurIPS 2024Stochastic Newton Proximal Extragradient Method
233. NeurIPS 2024Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data
234. NeurIPS 2024Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
235. NeurIPS 2024Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
236. NeurIPS 2024Stopping Bayesian Optimization with Probabilistic Regret Bounds
237. NeurIPS 2024Super Consistency of Neural Network Landscapes and Learning Rate Transfer
238. NeurIPS 2024SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
239. NeurIPS 2024Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
240. NeurIPS 2024The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
241. NeurIPS 2024The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
242. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
243. NeurIPS 2024The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
244. NeurIPS 2024The Implicit Bias of Adam on Separable Data
245. NeurIPS 2024The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
246. NeurIPS 2024The Power of Extrapolation in Federated Learning
247. NeurIPS 2024The Road Less Scheduled
248. NeurIPS 2024The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
249. NeurIPS 2024The Space Complexity of Approximating Logistic Loss
250. NeurIPS 2024The Star Geometry of Critic-Based Regularizer Learning

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.