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

286 papers, page 4 of 6

151. ICML 2026LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding
152. ICML 2026Local Constrained Bayesian Optimization
153. ICML 2026Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
154. ICML 2026Local-Minima-Preserving Polynomial Relaxation of Ising Problems
155. ICML 2026Lookahead Path Likelihood Optimization for Diffusion LLMs
156. ICML 2026Loss-Aware Distributionally Robust Optimization via Trainable Optimal Transport Ambiguity Sets
157. ICML 2026Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles
158. ICML 2026LS$^{2}$MC-GDA: A Smoothed Algorithm for Federated Stochastic Multi-Level Compositional Minimax Optimization
159. ICML 2026M+Adam: Low-Precision Training via Additive–Multiplicative Optimization
160. ICML 2026MaxSAT-Based Compression for Tsetlin Machines
161. ICML 2026Mean Flow Policy Optimization
162. ICML 2026Memory Savings at What Cost? A Study of Alternatives to Backpropagation
163. ICML 2026Meta-Black-Box Optimization Can Do Search Guidance for Expensive Constrained Multi-Objective Optimization
164. ICML 2026MineDraft: A Framework for Batch Parallel Speculative Decoding
165. ICML 2026MiniMax Learning of Interpretable Factored Stochastic Policies from Conjoint Data, with Uncertainty Quantification
166. ICML 2026Minimizing Upper Confidence Bounds: A Data-Driven Framework for Stochastic Programming
167. ICML 2026Mirror Descent Under Generalized Smoothness
168. ICML 2026Mirror Mean-Field Langevin Dynamics
169. ICML 2026Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation
170. ICML 2026MoSSP: A Momentum-Based Single-Loop Stochastic Penalty Method for Nonconvex Constrained DC-regularized Optimization
171. ICML 2026MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation Optimization
172. ICML 2026Multi-Objective Bayesian Optimization via Adaptive $\varepsilon$-Constraint Decomposition
173. ICML 2026Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation
174. ICML 2026Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation
175. ICML 2026Near-Optimal Convergence of Accelerated Gradient Methods under Generalized and $(L_0,L_1)$-Smoothness
176. ICML 2026Neural QAOA$^2$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
177. ICML 2026Noisy Pairwise-Comparison Random Search for Smooth Nonconvex Optimization
178. ICML 2026Non-Parametric Optimization for Scalable Learning in Stochastic Decision Problems
179. ICML 2026Nonconvex Low-Rank Tensor Representation with Deep Priors for Multiview Subspace Clustering
180. ICML 2026Normalized Rewards for Preference Optimization
181. ICML 2026Not All Answers Are Contextually Persuadable: Inference Dynamics in Large Language Models under Contextual Influence
182. ICML 2026Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
183. ICML 2026OLion: Approaching the Hadamard Ideal by Intersecting Spectral and L inf Implicit Biases
184. ICML 2026On Densest $k$-Subgraph Mining and Diagonal Loading: Optimization Landscape and Finite-Step Exact Convergence Analysis
185. ICML 2026On Regret Bounds of Thompson Sampling for Bayesian Optimization
186. ICML 2026On the Anisotropy of Score-Based Generative Models
187. ICML 2026On the Convergence of Decentralized Stochastic Minimax Optimization Algorithm with Compressed Communication
188. ICML 2026On the Convergence Rate of LoRA Gradient Descent
189. ICML 2026On the Optimization Trajectory of DeepWalk Embeddings
190. ICML 2026On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization
191. ICML 2026On the Role of Batch Size in Stochastic Conditional Gradient Methods
192. ICML 2026One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining
193. ICML 2026Operator Splitting with Hamilton-Jacobi-based Proximals
194. ICML 2026OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
195. ICML 2026Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verification
196. ICML 2026Optimal Anytime Algorithms for Online Convex Optimization with Adversarial Constraints
197. ICML 2026Optimal Regret for Policy Optimization in Contextual Bandits
198. ICML 2026Optimal Transport with Symmetry Groups
199. ICML 2026Optimal Transport–Guided Stochastic Control for Graph Combinatorial Optimization
200. ICML 2026OptMaster: A DAG-Based Framework for Formulation and Heuristic Discovery in 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.