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

98 papers, page 2 of 2

51. ICML 2023Global Optimization with Parametric Function Approximation
52. ICML 2023Graph Reinforcement Learning for Network Control via Bi-Level Optimization
53. ICML 2023High Probability Convergence of Stochastic Gradient Methods
54. ICML 2023High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance
55. ICML 2023Implicit Jacobian regularization weighted with impurity of probability output
56. ICML 2023Improving Bi-level Optimization Based Methods with Inspiration from Humans' Classroom Study Techniques
57. ICML 2023Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
58. ICML 2023Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement
59. ICML 2023Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach
60. ICML 2023Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability
61. ICML 2023Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set
62. ICML 2023Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions
63. ICML 2023Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
64. ICML 2023Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization
65. ICML 2023Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods
66. ICML 2023Nonparametric Iterative Machine Teaching
67. ICML 2023Omnipredictors for Constrained Optimization
68. ICML 2023On the Convergence of Federated Averaging with Cyclic Client Participation
69. ICML 2023On the Convergence of SARSA with Linear Function Approximation
70. ICML 2023On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm
71. ICML 2023On the Convergence Rate of Gaussianization with Random Rotations
72. ICML 2023On User-Level Private Convex Optimization
73. ICML 2023Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization
74. ICML 2023Optimal Shrinkage for Distributed Second-Order Optimization
75. ICML 2023Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization
76. ICML 2023Optimization for Amortized Inverse Problems
77. ICML 2023PASTA: Pessimistic Assortment Optimization
78. ICML 2023Quantized Distributed Training of Large Models with Convergence Guarantees
79. ICML 2023Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
80. ICML 2023Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds
81. ICML 2023Revisiting Domain Randomization via Relaxed State-Adversarial Policy Optimization
82. ICML 2023Revisiting Sampling for Combinatorial Optimization
83. ICML 2023Second-Order Optimization with Lazy Hessians
84. ICML 2023Self-Attention Amortized Distributional Projection Optimization for Sliced Wasserstein Point-Cloud Reconstruction
85. ICML 2023Semi Bandit dynamics in Congestion Games: Convergence to Nash Equilibrium and No-Regret Guarantees.
86. ICML 2023Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function
87. ICML 2023SLAMB: Accelerated Large Batch Training with Sparse Communication
88. ICML 2023Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels
89. ICML 2023Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks
90. ICML 2023Submodular Order Functions and Assortment Optimization
91. ICML 2023SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems
92. ICML 2023Target-based Surrogates for Stochastic Optimization
93. ICML 2023Tight Certification of Adversarially Trained Neural Networks via Nonconvex Low-Rank Semidefinite Relaxations
94. ICML 2023Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes
95. ICML 2023Transformer-based Stagewise Decomposition for Large-Scale Multistage Stochastic Optimization
96. ICML 2023Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy
97. ICML 2023Understand and Modularize Generator Optimization in ELECTRA-style Pretraining
98. ICML 2023User-level Private Stochastic Convex Optimization with Optimal Rates

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.