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 2 of 3

51. ICLR 2024Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
52. ICLR 2024L2P-MIP: Learning to Presolve for Mixed Integer Programming
53. ICLR 2024Language Model Decoding as Direct Metrics Optimization
54. ICLR 2024Large Language Models to Enhance Bayesian Optimization
55. ICLR 2024Learning model uncertainty as variance-minimizing instance weights
56. ICLR 2024Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model
57. ICLR 2024Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning
58. ICLR 2024Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset
59. ICLR 2024Linear attention is (maybe) all you need (to understand Transformer optimization)
60. ICLR 2024Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts
61. ICLR 2024Local Composite Saddle Point Optimization
62. ICLR 2024Magnitude Invariant Parametrizations Improve Hypernetwork Learning
63. ICLR 2024Massively Scalable Inverse Reinforcement Learning in Google Maps
64. ICLR 2024Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis
65. ICLR 2024Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes
66. ICLR 2024Momentum Benefits Non-iid Federated Learning Simply and Provably
67. ICLR 2024Near-Optimal Solutions of Constrained Learning Problems
68. ICLR 2024Neur2RO: Neural Two-Stage Robust Optimization
69. ICLR 2024Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
70. ICLR 2024New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions
71. ICLR 2024On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
72. ICLR 2024On Stationary Point Convergence of PPO-Clip
73. ICLR 2024On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
74. ICLR 2024On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback
75. ICLR 2024On the Parameterization of Second-Order Optimization Effective towards the Infinite Width
76. ICLR 2024One Forward is Enough for Neural Network Training via Likelihood Ratio Method
77. ICLR 2024Optimistic Bayesian Optimization with Unknown Constraints
78. ICLR 2024Order-Preserving GFlowNets
79. ICLR 2024Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization
80. ICLR 2024Private Zeroth-Order Nonsmooth Nonconvex Optimization
81. ICLR 2024PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
82. ICLR 2024Quality-Diversity through AI Feedback
83. ICLR 2024Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
84. ICLR 2024Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
85. ICLR 2024Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
86. ICLR 2024Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework
87. ICLR 2024Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
88. ICLR 2024Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
89. ICLR 2024Robust Model-Based Optimization for Challenging Fitness Landscapes
90. ICLR 2024Scaling Convex Neural Networks with Burer-Monteiro Factorization
91. ICLR 2024SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem
92. ICLR 2024Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity
93. ICLR 2024Small-scale proxies for large-scale Transformer training instabilities
94. ICLR 2024Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
95. ICLR 2024Statistical Rejection Sampling Improves Preference Optimization
96. ICLR 2024Submodular Reinforcement Learning
97. ICLR 2024Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems
98. ICLR 2024Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration
99. ICLR 2024Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks
100. ICLR 2024The importance of feature preprocessing for differentially private linear optimization

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.