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

154 papers, page 2 of 4

51. NeurIPS 2023Exponentially Convergent Algorithms for Supervised Matrix Factorization
52. NeurIPS 2023Failure-Aware Gaussian Process Optimization with Regret Bounds
53. NeurIPS 2023Fair Canonical Correlation Analysis
54. NeurIPS 2023FAMO: Fast Adaptive Multitask Optimization
55. NeurIPS 2023Fast Bellman Updates for Wasserstein Distributionally Robust MDPs
56. NeurIPS 2023Fast Partitioned Learned Bloom Filter
57. NeurIPS 2023Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
58. NeurIPS 2023Faster Margin Maximization Rates for Generic Optimization Methods
59. NeurIPS 2023Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
60. NeurIPS 2023Federated Conditional Stochastic Optimization
61. NeurIPS 2023Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
62. NeurIPS 2023FedNAR: Federated Optimization with Normalized Annealing Regularization
63. NeurIPS 2023Finding Local Minima Efficiently in Decentralized Optimization
64. NeurIPS 2023Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization
65. NeurIPS 2023First Order Stochastic Optimization with Oblivious Noise
66. NeurIPS 2023Fractal Landscapes in Policy Optimization
67. NeurIPS 2023Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization
68. NeurIPS 2023Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization
69. NeurIPS 2023Global Identifiability of $\ell_1$-based Dictionary Learning via Matrix Volume Optimization
70. NeurIPS 2023GloptiNets: Scalable Non-Convex Optimization with Certificates
71. NeurIPS 2023Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity
72. NeurIPS 2023Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures
73. NeurIPS 2023Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise
74. NeurIPS 2023Improving the Knowledge Gradient Algorithm
75. NeurIPS 2023Injecting Multimodal Information into Rigid Protein Docking via Bi-level Optimization
76. NeurIPS 2023Knowledge Distillation Performs Partial Variance Reduction
77. NeurIPS 2023L2T-DLN: Learning to Teach with Dynamic Loss Network
78. NeurIPS 2023Learning Cuts via Enumeration Oracles
79. NeurIPS 2023Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt
80. NeurIPS 2023Leveraging the two-timescale regime to demonstrate convergence of neural networks
81. NeurIPS 2023Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices
82. NeurIPS 2023Max-Margin Token Selection in Attention Mechanism
83. NeurIPS 2023Mechanic: A Learning Rate Tuner
84. NeurIPS 2023Memory-Constrained Algorithms for Convex Optimization
85. NeurIPS 2023MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning
86. NeurIPS 2023MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates
87. NeurIPS 2023Model-Based Control with Sparse Neural Dynamics
88. NeurIPS 2023Momentum Provably Improves Error Feedback!
89. NeurIPS 2023Neural Fields with Hard Constraints of Arbitrary Differential Order
90. NeurIPS 2023Non-Convex Bilevel Optimization with Time-Varying Objective Functions
91. NeurIPS 2023Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization
92. NeurIPS 2023On skip connections and normalisation layers in deep optimisation
93. NeurIPS 2023On the Generalization Error of Stochastic Mirror Descent for Quadratically-Bounded Losses: an Improved Analysis
94. NeurIPS 2023On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
95. NeurIPS 2023On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions
96. NeurIPS 2023One-step differentiation of iterative algorithms
97. NeurIPS 2023Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure
98. NeurIPS 2023Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
99. NeurIPS 2023Optimal Time Complexities of Parallel Stochastic Optimization Methods Under a Fixed Computation Model
100. NeurIPS 2023Optimization of Inter-group criteria for clustering with minimum size constraints

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.