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

107 papers, page 1 of 3

1. ICLR 2024A Discretization Framework for Robust Contextual Stochastic Optimization
2. ICLR 2024A Fast and Provable Algorithm for Sparse Phase Retrieval
3. ICLR 2024A General Framework for User-Guided Bayesian Optimization
4. ICLR 2024A Precise Characterization of SGD Stability Using Loss Surface Geometry
5. ICLR 2024A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
6. ICLR 2024A Probabilistic Framework for Modular Continual Learning
7. ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
8. ICLR 2024A Unified Framework for Bayesian Optimization under Contextual Uncertainty
9. ICLR 2024Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
10. ICLR 2024Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
11. ICLR 2024Accelerating Sinkhorn algorithm with sparse Newton iterations
12. ICLR 2024Adversarial Causal Bayesian Optimization
13. ICLR 2024An improved analysis of per-sample and per-update clipping in federated learning
14. ICLR 2024Backdoor Contrastive Learning via Bi-level Trigger Optimization
15. ICLR 2024Balancing Act: Constraining Disparate Impact in Sparse Models
16. ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
17. ICLR 2024Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
18. ICLR 2024Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
19. ICLR 2024Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
20. ICLR 2024Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression
21. ICLR 2024CO2: Efficient Distributed Training with Full Communication-Computation Overlap
22. ICLR 2024Combining Axes Preconditioners through Kronecker Approximation for Deep Learning
23. ICLR 2024Communication-Efficient Federated Non-Linear Bandit Optimization
24. ICLR 2024Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm
25. ICLR 2024Constraint-Free Structure Learning with Smooth Acyclic Orientations
26. ICLR 2024Convergence of Bayesian Bilevel Optimization
27. ICLR 2024Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
28. ICLR 2024DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training
29. ICLR 2024Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
30. ICLR 2024Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
31. ICLR 2024Distributionally Robust Optimization with Bias and Variance Reduction
32. ICLR 2024Doubly Robust Instance-Reweighted Adversarial Training
33. ICLR 2024Dropout Enhanced Bilevel Training
34. ICLR 2024EControl: Fast Distributed Optimization with Compression and Error Control
35. ICLR 2024Efficient Continual Finite-Sum Minimization
36. ICLR 2024Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants
37. ICLR 2024f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization
38. ICLR 2024Fast Equilibrium of SGD in Generic Situations
39. ICLR 2024FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
40. ICLR 2024Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
41. ICLR 2024Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem
42. ICLR 2024FOSI: Hybrid First and Second Order Optimization
43. ICLR 2024Global Optimality for Non-linear Constrained Restoration Problems via Invexity
44. ICLR 2024Gradual Optimization Learning for Conformational Energy Minimization
45. ICLR 2024Group Preference Optimization: Few-Shot Alignment of Large Language Models
46. ICLR 2024How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
47. ICLR 2024Implicit Maximum a Posteriori Filtering via Adaptive Optimization
48. ICLR 2024Implicit regularization of deep residual networks towards neural ODEs
49. ICLR 2024Improving Convergence and Generalization Using Parameter Symmetries
50. ICLR 2024Improving protein optimization with smoothed fitness landscapes

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.