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

178 papers, page 2 of 4

51. ICLR 2026Egalitarian Gradient Descent: A Simple Approach to Accelerated Grokking
52. ICLR 2026Entropic Confinement and Mode Connectivity in Overparameterized Neural Networks
53. ICLR 2026Error Feedback for Muon and Friends
54. ICLR 2026Fast Data Mixture Optimization via Gradient Descent
55. ICLR 2026Fast Frank–Wolfe Algorithms with Adaptive Bregman Step-Size for Weakly Convex Functions
56. ICLR 2026Faster Gradient Methods for Highly-smooth Stochastic Bilevel Optimization
57. ICLR 2026FastGRPO: Accelerating Policy Optimization via Concurrency-aware Speculative Decoding and Online Draft Learning
58. ICLR 2026FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
59. ICLR 2026FFT-based Dynamic Subspace Selection for Low-Rank Adaptive Optimization of Large Language Models
60. ICLR 2026Fine-tuning Quantized Neural Networks with Zeroth-order Optimization
61. ICLR 2026From Fields to Random Trees
62. ICLR 2026From Sequential to Parallel: Reformulating Dynamic Programming as GPU Kernels for Large-Scale Stochastic Combinatorial Optimization
63. ICLR 2026From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
64. ICLR 2026Gelato: Graph Edit Distance via Autoregressive Neural Combinatorial Optimization
65. ICLR 2026Generative Bayesian Optimization: Generative Models as Acquisition Functions
66. ICLR 2026Geometric-Mean Policy Optimization
67. ICLR 2026GIT-BO: High-Dimensional Bayesian Optimization with Tabular Foundation Models
68. ICLR 2026Global Resolution: Optimal Multi-Draft Speculative Sampling via Convex Optimization
69. ICLR 2026Globally aware optimization with resurgence
70. ICLR 2026GoalRank: Group-Relative Optimization for a Large Ranking Model
71. ICLR 2026Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region
72. ICLR 2026Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective
73. ICLR 2026Gradient-Normalized Smoothness for Optimization with Approximate Hessians
74. ICLR 2026Group Verification-based Policy Optimization for Interactive Coding Agents
75. ICLR 2026Group-Normalized Implicit Value Optimization for Language Models
76. ICLR 2026Guided Policy Optimization under Partial Observability
77. ICLR 2026Harmonized Cone for Feasible and Non-conflict Directions in Training Physics-Informed Neural Networks
78. ICLR 2026High Probability Bounds for Non-Convex Stochastic Optimization with Momentum
79. ICLR 2026High-Probability Bounds for the Last Iterate of Clipped SGD
80. ICLR 2026Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting
81. ICLR 2026How does the optimizer implicitly bias the model merging loss landscape?
82. ICLR 2026Implicit Bias and Loss of Plasticity in Matrix Completion: Depth Promotes Low-Rankness
83. ICLR 2026Improved $\ell_{p}$ Regression via Iteratively Reweighted Least Squares
84. ICLR 2026Improving Online-to-Nonconvex Conversion for Smooth Optimization via Double Optimism
85. ICLR 2026Incorporating Expert Priors into Bayesian Optimization via Dynamic Mean Decay
86. ICLR 2026Inpainting-Guided Policy Optimization for Diffusion Large Language Models
87. ICLR 2026Is On-Policy Data always the Best Choice for Direct Preference Optimization-Based LM Alignment?
88. ICLR 2026Joint Distribution–Informed Shapley Values for Sparse Counterfactual Explanations
89. ICLR 2026Keep the Best, Forget the Rest: Reliable Alignment with Order-Aware Preference Optimization
90. ICLR 2026Landing with the Score: Riemannian Optimization through Denoising
91. ICLR 2026Latent Thinking Optimization: Your Latent Reasoning Language Model Secretly Encodes Reward Signals in its Latent Thoughts
92. ICLR 2026Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization
93. ICLR 2026Learning More with Less: A Dynamic Dual-Level Down-Sampling Framework for Efficient Policy Optimization
94. ICLR 2026Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme
95. ICLR 2026Learning to Segment for Vehicle Routing Problems
96. ICLR 2026Lifelong Learning with Behavior Consolidation for Vehicle Routing
97. ICLR 2026LMask: Learn to Solve Constrained Routing Problems with Lazy Masking
98. ICLR 2026Local Entropy Search over Descent Sequences for Bayesian Optimization
99. ICLR 2026Machine Unlearning under Retain–Forget Entanglement
100. ICLR 2026MaskInversion: Localized Embeddings via Optimization of Explainability Maps

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.