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 1 of 6

1. ICML 2026$\alpha$-PFN: Fast Entropy Search via In-Context Learning
2. ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
3. ICML 2026$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
4. ICML 2026A Constrained Optimization Perspective of Unrolled Transformers
5. ICML 2026A Fully First-Order Layer for Differentiable Optimization
6. ICML 2026A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention
7. ICML 2026A Language-Guided Bayesian Optimization for Efficient LoRA Hyperparameter Search
8. ICML 2026A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost
9. ICML 2026A proximal ADMM for multiblock problems with block anti-upper triangular constraints
10. ICML 2026A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms
11. ICML 2026A Solver-Free Training Method for Predict-then-Optimize
12. ICML 2026A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization
13. ICML 2026A Tight Theory of Error Feedback Algorithms in Distributed Optimization
14. ICML 2026Accelerated and Stable Convergence with Anchored Generalized Optimistic Method
15. ICML 2026Accelerated Dual Method for Distributed Optimization: An Inexact-Gradient View of Local Updates
16. ICML 2026Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization
17. ICML 2026Achieving Structurally Robust Gromov Wasserstein Distance via Adaptive Dual-Mask
18. ICML 2026Adapting to Evolving Graphs: A Scalable Framework for Dynamic Coarsening
19. ICML 2026Adaptive Momentum and Nonlinear Damping for Neural Network Training
20. ICML 2026Adaptive Sharpness-Aware Minimization with a Polyak-type Step size: A Theory-Grounded Scheduler
21. ICML 2026AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning
22. ICML 2026ALAS: Additive Learnable Alpha-Stable Kernels for Flexible Bayesian Optimization
23. ICML 2026All ERMs Can Fail in Stochastic Convex Optimization Lower Bounds in Linear Dimension
24. ICML 2026AMDP: Asynchronous Multi-Directional Pipeline Parallelism for Large-Scale Models Training
25. ICML 2026An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale
26. ICML 2026An Exploration of Non-Euclidean Gradient Descent: Muon and its Many Variants
27. ICML 2026An Exterior Method for Nonnegative Matrix Factorization
28. ICML 2026ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization
29. ICML 2026Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization
30. ICML 2026Autoregressive Direct Preference Optimization
31. ICML 2026Balanced LoRA: Removing Parameter Invariance to Accelerate Convergence
32. ICML 2026Bilevel Optimization over Saddle Points of Zero-Sum Markov Games
33. ICML 2026Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning
34. ICML 2026Boosting CVaR Policy Optimization with Quantile Gradients
35. ICML 2026Bregman meets Lévy: Stochastic Mirror Descent with Heavy-Tailed Noise in Continuous and Discrete Time
36. ICML 2026Bridging Spherical Black-Box Optimizers
37. ICML 2026Can Adaptive Gradient Methods Converge under Heavy-Tailed Noise? A Case Study of AdaGrad
38. ICML 2026Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?
39. ICML 2026Certificate-Guided Pruning for Stochastic Lipschitz Optimization
40. ICML 2026CIRBench: Evaluating Large Language Models as LLVM IR Optimizers
41. ICML 2026Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers
42. ICML 2026Compact Conformal Subgraphs
43. ICML 2026Complexity of Decentralized Optimization with Mixed Affine Constraints
44. ICML 2026Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization
45. ICML 2026Conformal Prediction for Early Stopping in Mixed Integer Optimization
46. ICML 2026Constructing Industrial-Scale Optimization Modeling Benchmark
47. ICML 2026Context Tuning for In-Context Optimization
48. ICML 2026Convergence Analysis of Decentralized Hessian-/Jacobian-Free Algorithm for Nonconvex Stochastic Bilevel Optimization
49. ICML 2026Convergence Analysis of the Lion Optimizer in Centralized and Distributed Settings
50. ICML 2026Convergence of Steepest Descent and Adam under Non-Uniform Smoothness

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.