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

958 papers, page 15 of 20

701. NeurIPS 2024On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization
702. NeurIPS 2024Online Composite Optimization Between Stochastic and Adversarial Environments
703. NeurIPS 2024OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
704. NeurIPS 2024Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
705. NeurIPS 2024Optimal Scalarizations for Sublinear Hypervolume Regret
706. NeurIPS 2024Optimization Algorithm Design via Electric Circuits
707. NeurIPS 2024Optimization Can Learn Johnson Lindenstrauss Embeddings
708. NeurIPS 2024Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition
709. NeurIPS 2024Ordered Momentum for Asynchronous SGD
710. NeurIPS 2024OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation
711. NeurIPS 2024Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport
712. NeurIPS 2024Parameter-free Clipped Gradient Descent Meets Polyak
713. NeurIPS 2024Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds
714. NeurIPS 2024Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization
715. NeurIPS 2024Policy Mirror Descent with Lookahead
716. NeurIPS 2024Policy Optimization for Robust Average Reward MDPs
717. NeurIPS 2024Practical $0.385$-Approximation for Submodular Maximization Subject to a Cardinality Constraint
718. NeurIPS 2024Private Geometric Median
719. NeurIPS 2024Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
720. NeurIPS 2024Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
721. NeurIPS 2024Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
722. NeurIPS 2024Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
723. NeurIPS 2024Public-data Assisted Private Stochastic Optimization: Power and Limitations
724. NeurIPS 2024Quantitative Convergences of Lie Group Momentum Optimizers
725. NeurIPS 2024Random Function Descent
726. NeurIPS 2024Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy
727. NeurIPS 2024Recurrent neural networks: vanishing and exploding gradients are not the end of the story
728. NeurIPS 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
729. NeurIPS 2024Regularized Q-Learning
730. NeurIPS 2024Rejection via Learning Density Ratios
731. NeurIPS 2024ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
732. NeurIPS 2024Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
733. NeurIPS 2024Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
734. NeurIPS 2024Resolving Discrepancies in Compute-Optimal Scaling of Language Models
735. NeurIPS 2024Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
736. NeurIPS 2024Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
737. NeurIPS 2024Robust Gaussian Processes via Relevance Pursuit
738. NeurIPS 2024Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
739. NeurIPS 2024S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization
740. NeurIPS 2024Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
741. NeurIPS 2024Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
742. NeurIPS 2024Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
743. NeurIPS 2024Scalable Kernel Inverse Optimization
744. NeurIPS 2024Scalable Optimization in the Modular Norm
745. NeurIPS 2024Second-order forward-mode optimization of recurrent neural networks for neuroscience
746. NeurIPS 2024Semidefinite Relaxations of the Gromov-Wasserstein Distance
747. NeurIPS 2024SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
748. NeurIPS 2024Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
749. NeurIPS 2024Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization
750. NeurIPS 2024Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance

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.