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

160 papers, page 1 of 4

1. ICML 2024A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
2. ICML 2024A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
3. ICML 2024A Geometric Decomposition of Finite Games: Convergence vs. Recurrence under Exponential Weights
4. ICML 2024A Global Geometric Analysis of Maximal Coding Rate Reduction
5. ICML 2024A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
6. ICML 2024A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
7. ICML 2024A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
8. ICML 2024A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
9. ICML 2024A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles
10. ICML 2024Absolute Policy Optimization: Enhancing Lower Probability Bound of Performance with High Confidence
11. ICML 2024Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
12. ICML 2024Accelerating Convergence of Score-Based Diffusion Models, Provably
13. ICML 2024Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
14. ICML 2024ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints
15. ICML 2024Activation-Descent Regularization for Input Optimization of ReLU Networks
16. ICML 2024Adaptive-Gradient Policy Optimization: Enhancing Policy Learning in Non-Smooth Differentiable Simulations
17. ICML 2024Advancing Dynamic Sparse Training by Exploring Optimization Opportunities
18. ICML 2024An Iterative Min-Min Optimization Method for Sparse Bayesian Learning
19. ICML 2024An Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization
20. ICML 2024Autonomous Sparse Mean-CVaR Portfolio Optimization
21. ICML 2024Barrier Algorithms for Constrained Non-Convex Optimization
22. ICML 2024Bayesian Optimization of Function Networks with Partial Evaluations
23. ICML 2024Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
24. ICML 2024Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
25. ICML 2024BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation
26. ICML 2024Boosting Offline Optimizers with Surrogate Sensitivity
27. ICML 2024BOtied: Multi-objective Bayesian optimization with tied multivariate ranks
28. ICML 2024Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints
29. ICML 2024Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
30. ICML 2024Challenges in Training PINNs: A Loss Landscape Perspective
31. ICML 2024Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
32. ICML 2024Compact Optimality Verification for Optimization Proxies
33. ICML 2024Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation
34. ICML 2024Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms
35. ICML 2024Convergence and Trade-Offs in Riemannian Gradient Descent and Riemannian Proximal Point
36. ICML 2024Convergence Guarantees for the DeepWalk Embedding on Block Models
37. ICML 2024Convergence of Some Convex Message Passing Algorithms to a Fixed Point
38. ICML 2024Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning
39. ICML 2024Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
40. ICML 2024Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers
41. ICML 2024Deconstructing the Goldilocks Zone of Neural Network Initialization
42. ICML 2024Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration
43. ICML 2024Delving into the Convergence of Generalized Smooth Minimax Optimization
44. ICML 2024Differentiability and Optimization of Multiparameter Persistent Homology
45. ICML 2024Differentiable Distributionally Robust Optimization Layers
46. ICML 2024Differentiable Mapper for Topological Optimization of Data Representation
47. ICML 2024Distributed Bilevel Optimization with Communication Compression
48. ICML 2024Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification
49. ICML 2024Double Momentum Method for Lower-Level Constrained Bilevel Optimization
50. ICML 2024Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient

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.