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 6 of 15

251. ICML 2026Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
252. ICML 2026Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise
253. ICML 2026Step-Size Stability in Stochastic Optimization: A Theoretical Perspective
254. ICML 2026STLA: Spatiotemporal Lookahead Alignment for Post-Training Quantization
255. ICML 2026Stochastic Gradient Methods under Heavy-Tailed Noises in Weakly Convex Optimization
256. ICML 2026Submodular Optimization for Minimal Augmentation in Robust Language Model Alignment
257. ICML 2026Success-Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success
258. ICML 2026Support-Proximity Augmented Diffusion Estimation for Offline Black-Box Optimization
259. ICML 2026Taking the GP Out of the Loop
260. ICML 2026Taming Stochastic Gradient Descent: Almost Sure Convergence and Saddle-Point Avoidance under $(L_{0},L_{1})$-Smoothness
261. ICML 2026Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space
262. ICML 2026The Differences Between Direct Alignment Algorithms are a Blur
263. ICML 2026The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
264. ICML 2026Theoretical Analysis of Sparse Optimization with Reparameterization, Weight Decay, and Adaptive Learning Rate
265. ICML 2026Theoretical Challenges in Learning for Branch-and-Cut
266. ICML 2026TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization
267. ICML 2026Tournament Style RL: Stabilizing Policy Optimization on Non Verifiable Problems
268. ICML 2026Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner
269. ICML 2026Towards Fully Parameter-Free Stochastic Optimization: Grid Search with Self-Bounding Analysis
270. ICML 2026Towards Parameter-Free Temporal Difference Learning
271. ICML 2026Trainable Nonexpansive Denoisers for Contractive Image Reconstruction
272. ICML 2026Training Prompt Matters: State-Adaptive Optimization for Robust Fine-Tuning
273. ICML 2026Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
274. ICML 2026TSP with Predictions: Heatmap to Tour with Provable Guarantees
275. ICML 2026TurboGS: Accelerating 3D Gaussian Splatting via Error-Guided Sparse Pixel Sampling and Optimization
276. ICML 2026Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
277. ICML 2026UCPO: Uncertainty-Aware Policy Optimization
278. ICML 2026Unbiased Principles, Robust Rewards
279. ICML 2026UniDrag: Unified Multi-Field Prediction and Robust Shape Optimization for Vehicle Aerodynamics
280. ICML 2026Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
281. ICML 2026Variable Clustering via Distributionally Robust Nodewise Regression
282. ICML 2026Variational inference via Gaussian interacting particles in the Bures-Wasserstein geometry
283. ICML 2026Weight Decay Improves Language Model Plasticity
284. ICML 2026Why Do We Need Warm-up? A Theoretical Perspective
285. ICML 2026Zeroth-Order Forward-Only SNN Training Inspiring Neuromorphic On-Chip Learning
286. ICML 2026Zeroth-Order Optimization at the Edge of Stability
287. ICML 2025A Bregman Proximal Viewpoint on Neural Operators
288. ICML 2025A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
289. ICML 2025A First-order Generative Bilevel Optimization Framework for Diffusion Models
290. ICML 2025A Generalization Result for Convergence in Learning-to-Optimize
291. ICML 2025A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models
292. ICML 2025A Near Linear Query Lower Bound for Submodular Maximization
293. ICML 2025A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
294. ICML 2025A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
295. ICML 2025A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization
296. ICML 2025Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
297. ICML 2025Achieving Linear Speedup and Near-Optimal Complexity for Decentralized Optimization over Row-stochastic Networks
298. ICML 2025Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
299. ICML 2025Adaptive Partitioning Schemes for Optimistic Optimization
300. ICML 2025Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference 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.