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

2,330 papers, page 36 of 47

1751. NeurIPS 2024Constrained Binary Decision Making
1752. NeurIPS 2024Constrained Diffusion Models via Dual Training
1753. NeurIPS 2024Contextual Linear Optimization with Bandit Feedback
1754. NeurIPS 2024Controlling Continuous Relaxation for Combinatorial Optimization
1755. NeurIPS 2024Convergence Analysis of Split Federated Learning on Heterogeneous Data
1756. NeurIPS 2024Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods
1757. NeurIPS 2024CRAYM: Neural Field Optimization via Camera RAY Matching
1758. NeurIPS 2024Decision-Focused Learning with Directional Gradients
1759. NeurIPS 2024Deep Learning for Computing Convergence Rates of Markov Chains
1760. NeurIPS 2024Deep linear networks for regression are implicitly regularized towards flat minima
1761. NeurIPS 2024DePLM: Denoising Protein Language Models for Property Optimization
1762. NeurIPS 2024Derivatives of Stochastic Gradient Descent in parametric optimization
1763. NeurIPS 2024DG-SLAM: Robust Dynamic Gaussian Splatting SLAM with Hybrid Pose Optimization
1764. NeurIPS 2024Diffeomorphic interpolation for efficient persistence-based topological optimization
1765. NeurIPS 2024Differentially Private Optimization with Sparse Gradients
1766. NeurIPS 2024Diffusion-based Reinforcement Learning via Q-weighted Variational Policy Optimization
1767. NeurIPS 2024DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
1768. NeurIPS 2024Direct Preference-Based Evolutionary Multi-Objective Optimization with Dueling Bandits
1769. NeurIPS 2024Directional Smoothness and Gradient Methods: Convergence and Adaptivity
1770. NeurIPS 2024Discovering Preference Optimization Algorithms with and for Large Language Models
1771. NeurIPS 2024Discretely beyond $1/e$: Guided Combinatorial Algortihms for Submodular Maximization
1772. NeurIPS 2024Disentangling Linear Quadratic Control with Untrusted ML Predictions
1773. NeurIPS 2024Don't Compress Gradients in Random Reshuffling: Compress Gradient Differences
1774. NeurIPS 2024Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
1775. NeurIPS 2024Dual Lagrangian Learning for Conic Optimization
1776. NeurIPS 2024Dual-frame Fluid Motion Estimation with Test-time Optimization and Zero-divergence Loss
1777. NeurIPS 2024e-COP : Episodic Constrained Optimization of Policies
1778. NeurIPS 2024Efficient Combinatorial Optimization via Heat Diffusion
1779. NeurIPS 2024Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
1780. NeurIPS 2024Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization
1781. NeurIPS 2024Efficient Prompt Optimization Through the Lens of Best Arm Identification
1782. NeurIPS 2024Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
1783. NeurIPS 2024EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
1784. NeurIPS 2024Emergence of heavy tails in homogenized stochastic gradient descent
1785. NeurIPS 2024Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
1786. NeurIPS 2024Exploring Fixed Point in Image Editing: Theoretical Support and Convergence Optimization
1787. NeurIPS 2024Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
1788. NeurIPS 2024Fair Wasserstein Coresets
1789. NeurIPS 2024Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets
1790. NeurIPS 2024Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
1791. NeurIPS 2024Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
1792. NeurIPS 2024Faster Algorithms for User-Level Private Stochastic Convex Optimization
1793. NeurIPS 2024FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
1794. NeurIPS 2024Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
1795. NeurIPS 2024Finding Transformer Circuits With Edge Pruning
1796. NeurIPS 2024Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random
1797. NeurIPS 2024First-Order Methods for Linearly Constrained Bilevel Optimization
1798. NeurIPS 2024First-Order Minimax Bilevel Optimization
1799. NeurIPS 2024Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
1800. NeurIPS 2024Functional Bilevel Optimization for Machine Learning

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.