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

275 papers, page 2 of 6

51. NeurIPS 2024Deep linear networks for regression are implicitly regularized towards flat minima
52. NeurIPS 2024DePLM: Denoising Protein Language Models for Property Optimization
53. NeurIPS 2024Derivatives of Stochastic Gradient Descent in parametric optimization
54. NeurIPS 2024DG-SLAM: Robust Dynamic Gaussian Splatting SLAM with Hybrid Pose Optimization
55. NeurIPS 2024Diffeomorphic interpolation for efficient persistence-based topological optimization
56. NeurIPS 2024Differentially Private Optimization with Sparse Gradients
57. NeurIPS 2024Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
58. NeurIPS 2024DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
59. NeurIPS 2024Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits
60. NeurIPS 2024Directional Smoothness and Gradient Methods: Convergence and Adaptivity
61. NeurIPS 2024Discovering Preference Optimization Algorithms with and for Large Language Models
62. NeurIPS 2024Discretely beyond $1/e$: Guided Combinatorial Algortihms for Submodular Maximization
63. NeurIPS 2024Disentangling Linear Quadratic Control with Untrusted ML Predictions
64. NeurIPS 2024Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences
65. NeurIPS 2024Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
66. NeurIPS 2024Dual Lagrangian Learning for Conic Optimization
67. NeurIPS 2024Dual-frame Fluid Motion Estimation with Test-time Optimization and Zero-divergence Loss
68. NeurIPS 2024e-COP : Episodic Constrained Optimization of Policies
69. NeurIPS 2024Efficient Combinatorial Optimization via Heat Diffusion
70. NeurIPS 2024Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
71. NeurIPS 2024Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization
72. NeurIPS 2024Efficient Prompt Optimization Through the Lens of Best Arm Identification
73. NeurIPS 2024Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
74. NeurIPS 2024EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
75. NeurIPS 2024Emergence of heavy tails in homogenized stochastic gradient descent
76. NeurIPS 2024Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
77. NeurIPS 2024Exploring Fixed Point in Image Editing: Theoretical Support and Convergence Optimization
78. NeurIPS 2024Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
79. NeurIPS 2024Fair Wasserstein Coresets
80. NeurIPS 2024Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets
81. NeurIPS 2024Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
82. NeurIPS 2024Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
83. NeurIPS 2024Faster Algorithms for User-Level Private Stochastic Convex Optimization
84. NeurIPS 2024FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
85. NeurIPS 2024Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
86. NeurIPS 2024Finding Transformer Circuits With Edge Pruning
87. NeurIPS 2024Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random
88. NeurIPS 2024First-Order Methods for Linearly Constrained Bilevel Optimization
89. NeurIPS 2024First-Order Minimax Bilevel Optimization
90. NeurIPS 2024Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
91. NeurIPS 2024Functional Bilevel Optimization for Machine Learning
92. NeurIPS 2024Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem
93. NeurIPS 2024Fundamental Convergence Analysis of Sharpness-Aware Minimization
94. NeurIPS 2024Generalized Fast Exact Conformalization
95. NeurIPS 2024Geodesic Optimization for Predictive Shift Adaptation on EEG data
96. NeurIPS 2024Gliding over the Pareto Front with Uniform Designs
97. NeurIPS 2024Global Convergence in Training Large-Scale Transformers
98. NeurIPS 2024Globally Convergent Variational Inference
99. NeurIPS 2024Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
100. NeurIPS 2024Gradient Guidance for Diffusion Models: An Optimization Perspective

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.