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

79 papers, page 1 of 2

1. ICLR 2023$\Lambda$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells
2. ICLR 2023A view of mini-batch SGD via generating functions: conditions of convergence, phase transitions, benefit from negative momenta.
3. ICLR 2023Accelerated Single-Call Methods for Constrained Min-Max Optimization
4. ICLR 2023Adaptive Optimization in the $\infty$-Width Limit
5. ICLR 2023AGRO: Adversarial discovery of error-prone Groups for Robust Optimization
6. ICLR 2023Alternating Differentiation for Optimization Layers
7. ICLR 2023Approximate Vanishing Ideal Computations at Scale
8. ICLR 2023Asynchronous Distributed Bilevel Optimization
9. ICLR 2023Automating Nearest Neighbor Search Configuration with Constrained Optimization
10. ICLR 2023BALTO: fast tensor program optimization with diversity-based active learning
11. ICLR 2023Behind the Scenes of Gradient Descent: A Trajectory Analysis via Basis Function Decomposition
12. ICLR 2023Betty: An Automatic Differentiation Library for Multilevel Optimization
13. ICLR 2023Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD
14. ICLR 2023Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients
15. ICLR 2023Breaking Correlation Shift via Conditional Invariant Regularizer
16. ICLR 2023Conservative Bayesian Model-Based Value Expansion for Offline Policy Optimization
17. ICLR 2023Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
18. ICLR 2023DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle Complexity
19. ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
20. ICLR 2023Depth Separation with Multilayer Mean-Field Networks
21. ICLR 2023Differentially Private Adaptive Optimization with Delayed Preconditioners
22. ICLR 2023Discovering Evolution Strategies via Meta-Black-Box Optimization
23. ICLR 2023Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality
24. ICLR 2023Distributionally Robust Recourse Action
25. ICLR 2023Efficient Offline Policy Optimization with a Learned Model
26. ICLR 2023Efficiently Controlling Multiple Risks with Pareto Testing
27. ICLR 2023Ensuring DNN Solution Feasibility for Optimization Problems with Linear Constraints
28. ICLR 2023EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data
29. ICLR 2023Equivariance-aware Architectural Optimization of Neural Networks
30. ICLR 2023Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation
31. ICLR 2023Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods
32. ICLR 2023Faster federated optimization under second-order similarity
33. ICLR 2023Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
34. ICLR 2023FedExP: Speeding Up Federated Averaging via Extrapolation
35. ICLR 2023Fisher-Legendre (FishLeg) optimization of deep neural networks
36. ICLR 2023Globally Optimal Training of Neural Networks with Threshold Activation Functions
37. ICLR 2023Graph-based Deterministic Policy Gradient for Repetitive Combinatorial Optimization Problems
38. ICLR 2023Guarded Policy Optimization with Imperfect Online Demonstrations
39. ICLR 2023Hyperparameter Optimization through Neural Network Partitioning
40. ICLR 2023Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data
41. ICLR 2023Improved Convergence of Differential Private SGD with Gradient Clipping
42. ICLR 2023Improving Object-centric Learning with Query Optimization
43. ICLR 2023Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
44. ICLR 2023Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent
45. ICLR 2023Mind the Gap: Offline Policy Optimization for Imperfect Rewards
46. ICLR 2023Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach
47. ICLR 2023Model-based Causal Bayesian Optimization
48. ICLR 2023Multi-objective optimization via equivariant deep hypervolume approximation
49. ICLR 2023Noise Is Not the Main Factor Behind the Gap Between Sgd and Adam on Transformers, But Sign Descent Might Be
50. ICLR 2023On amortizing convex conjugates for optimal transport

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.