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

560 papers, page 10 of 12

451. NeurIPS 2024Non-geodesically-convex optimization in the Wasserstein space
452. NeurIPS 2024Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
453. NeurIPS 2024Normalization and effective learning rates in reinforcement learning
454. NeurIPS 2024Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers
455. NeurIPS 2024On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
456. NeurIPS 2024On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
457. NeurIPS 2024On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization
458. NeurIPS 2024Online Composite Optimization Between Stochastic and Adversarial Environments
459. NeurIPS 2024OptEx: Expediting First-Order Optimization with Approximately Parallelized Iterations
460. NeurIPS 2024Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
461. NeurIPS 2024Optimal Scalarizations for Sublinear Hypervolume Regret
462. NeurIPS 2024Optimization Algorithm Design via Electric Circuits
463. NeurIPS 2024Optimization Can Learn Johnson Lindenstrauss Embeddings
464. NeurIPS 2024Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition
465. NeurIPS 2024Ordered Momentum for Asynchronous SGD
466. NeurIPS 2024OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation
467. NeurIPS 2024Outlier-Robust Distributionally Robust Optimization via Unbalanced Optimal Transport
468. NeurIPS 2024Parameter-free Clipped Gradient Descent Meets Polyak
469. NeurIPS 2024Penalty-based Methods for Simple Bilevel Optimization under Hölderian Error Bounds
470. NeurIPS 2024Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization
471. NeurIPS 2024Policy Mirror Descent with Lookahead
472. NeurIPS 2024Policy Optimization for Robust Average Reward MDPs
473. NeurIPS 2024Practical $0.385$-Approximation for Submodular Maximization Subject to a Cardinality Constraint
474. NeurIPS 2024Private Geometric Median
475. NeurIPS 2024Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
476. NeurIPS 2024Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
477. NeurIPS 2024Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks
478. NeurIPS 2024Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
479. NeurIPS 2024Public-data Assisted Private Stochastic Optimization: Power and Limitations
480. NeurIPS 2024Quantitative Convergences of Lie Group Momentum Optimizers
481. NeurIPS 2024Random Function Descent
482. NeurIPS 2024Randomized Sparse Matrix Compression for Large-Scale Constrained Optimization in Cancer Radiotherapy
483. NeurIPS 2024Recurrent neural networks: vanishing and exploding gradients are not the end of the story
484. NeurIPS 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
485. NeurIPS 2024Regularized Q-Learning
486. NeurIPS 2024Rejection via Learning Density Ratios
487. NeurIPS 2024ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization
488. NeurIPS 2024Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad
489. NeurIPS 2024Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
490. NeurIPS 2024Resolving Discrepancies in Compute-Optimal Scaling of Language Models
491. NeurIPS 2024Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
492. NeurIPS 2024Revive Re-weighting in Imbalanced Learning by Density Ratio Estimation
493. NeurIPS 2024Robust Gaussian Processes via Relevance Pursuit
494. NeurIPS 2024Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
495. NeurIPS 2024S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization
496. NeurIPS 2024Safe and Sparse Newton Method for Entropic-Regularized Optimal Transport
497. NeurIPS 2024Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization
498. NeurIPS 2024Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
499. NeurIPS 2024Scalable Kernel Inverse Optimization
500. NeurIPS 2024Scalable Optimization in the Modular Norm

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.