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 13 of 20

601. NeurIPS 2024Efficient Prompt Optimization Through the Lens of Best Arm Identification
602. NeurIPS 2024Efficient Sign-Based Optimization: Accelerating Convergence via Variance Reduction
603. NeurIPS 2024EffiLearner: Enhancing Efficiency of Generated Code via Self-Optimization
604. NeurIPS 2024Emergence of heavy tails in homogenized stochastic gradient descent
605. NeurIPS 2024Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization
606. NeurIPS 2024Exploring Fixed Point in Image Editing: Theoretical Support and Convergence Optimization
607. NeurIPS 2024Exploring Jacobian Inexactness in Second-Order Methods for Variational Inequalities: Lower Bounds, Optimal Algorithms and Quasi-Newton Approximations
608. NeurIPS 2024Fair Wasserstein Coresets
609. NeurIPS 2024Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets
610. NeurIPS 2024Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
611. NeurIPS 2024Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints
612. NeurIPS 2024Faster Algorithms for User-Level Private Stochastic Convex Optimization
613. NeurIPS 2024FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
614. NeurIPS 2024Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis
615. NeurIPS 2024Finding Transformer Circuits With Edge Pruning
616. NeurIPS 2024Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random
617. NeurIPS 2024First-Order Methods for Linearly Constrained Bilevel Optimization
618. NeurIPS 2024First-Order Minimax Bilevel Optimization
619. NeurIPS 2024Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations
620. NeurIPS 2024Functional Bilevel Optimization for Machine Learning
621. NeurIPS 2024Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem
622. NeurIPS 2024Fundamental Convergence Analysis of Sharpness-Aware Minimization
623. NeurIPS 2024Generalized Fast Exact Conformalization
624. NeurIPS 2024Geodesic Optimization for Predictive Shift Adaptation on EEG data
625. NeurIPS 2024Gliding over the Pareto Front with Uniform Designs
626. NeurIPS 2024Global Convergence in Training Large-Scale Transformers
627. NeurIPS 2024Globally Convergent Variational Inference
628. NeurIPS 2024Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
629. NeurIPS 2024Gradient Guidance for Diffusion Models: An Optimization Perspective
630. NeurIPS 2024Gradient-Free Methods for Nonconvex Nonsmooth Stochastic Compositional Optimization
631. NeurIPS 2024Great Minds Think Alike: The Universal Convergence Trend of Input Salience
632. NeurIPS 2024Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame
633. NeurIPS 2024Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models
634. NeurIPS 2024High-probability complexity bounds for stochastic non-convex minimax optimization
635. NeurIPS 2024How Does Black-Box Impact the Learning Guarantee of Stochastic Compositional Optimization?
636. NeurIPS 2024How does Gradient Descent Learn Features --- A Local Analysis for Regularized Two-Layer Neural Networks
637. NeurIPS 2024How does PDE order affect the convergence of PINNs?
638. NeurIPS 2024Implicit Optimization Bias of Next-token Prediction in Linear Models
639. NeurIPS 2024Implicit Regularization of Decentralized Gradient Descent for Sparse Regression
640. NeurIPS 2024Improved Particle Approximation Error for Mean Field Neural Networks
641. NeurIPS 2024Improved Regret for Bandit Convex Optimization with Delayed Feedback
642. NeurIPS 2024Improving Deep Learning Optimization through Constrained Parameter Regularization
643. NeurIPS 2024Improving Equivariant Model Training via Constraint Relaxation
644. NeurIPS 2024Improving Generalization and Convergence by Enhancing Implicit Regularization
645. NeurIPS 2024Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity
646. NeurIPS 2024In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization
647. NeurIPS 2024In-Context Learning State Vector with Inner and Momentum Optimization
648. NeurIPS 2024Incorporating Test-Time Optimization into Training with Dual Networks for Human Mesh Recovery
649. NeurIPS 2024Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence
650. NeurIPS 2024Inversion-based Latent Bayesian Optimization

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.