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

736 papers, page 12 of 15

551. ICML 2024ILILT: Implicit Learning of Inverse Lithography Technologies
552. ICML 2024Implicit Bias of AdamW: $\ell_\infty$-Norm Constrained Optimization
553. ICML 2024Improved Differentially Private and Lazy Online Convex Optimization: Lower Regret without Smoothness Requirements
554. ICML 2024Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization
555. ICML 2024Improving SAM Requires Rethinking its Optimization Formulation
556. ICML 2024In-context Convergence of Transformers
557. ICML 2024In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
558. ICML 2024InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
559. ICML 2024Interpreting and Improving Diffusion Models from an Optimization Perspective
560. ICML 2024Iterative Regularized Policy Optimization with Imperfect Demonstrations
561. ICML 2024Joint Composite Latent Space Bayesian Optimization
562. ICML 2024KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions
563. ICML 2024LASER: Linear Compression in Wireless Distributed Optimization
564. ICML 2024Learning to Remove Cuts in Integer Linear Programming
565. ICML 2024Learning with 3D rotations, a hitchhiker's guide to SO(3)
566. ICML 2024Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
567. ICML 2024Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
568. ICML 2024LPGD: A General Framework for Backpropagation through Embedded Optimization Layers
569. ICML 2024MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
570. ICML 2024Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization
571. ICML 2024MLI Formula: A Nearly Scale-Invariant Solution with Noise Perturbation
572. ICML 2024Model Alignment as Prospect Theoretic Optimization
573. ICML 2024Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-Loop and Hessian-Free Solution Strategy
574. ICML 2024No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
575. ICML 2024Non-convex Stochastic Composite Optimization with Polyak Momentum
576. ICML 2024Non-stationary Online Convex Optimization with Arbitrary Delays
577. ICML 2024Offline Multi-Objective Optimization
578. ICML 2024On Convergence of Incremental Gradient for Non-convex Smooth Functions
579. ICML 2024On Discrete Prompt Optimization for Diffusion Models
580. ICML 2024On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization
581. ICML 2024On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
582. ICML 2024On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
583. ICML 2024On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
584. ICML 2024On the Last-Iterate Convergence of Shuffling Gradient Methods
585. ICML 2024Optimal Differentially Private Model Training with Public Data
586. ICML 2024Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
587. ICML 2024Optimization without Retraction on the Random Generalized Stiefel Manifold
588. ICML 2024Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks
589. ICML 2024Plug-in Performative Optimization
590. ICML 2024Position: Leverage Foundational Models for Black-Box Optimization
591. ICML 2024Position: Optimization in SciML Should Employ the Function Space Geometry
592. ICML 2024Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
593. ICML 2024Principled Preferential Bayesian Optimization
594. ICML 2024Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
595. ICML 2024Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
596. ICML 2024Proactive DP: A Multiple Target Optimization Framework for DP-SGD
597. ICML 2024Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization
598. ICML 2024Projection-Free Online Convex Optimization with Time-Varying Constraints
599. ICML 2024Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
600. ICML 2024Quantum Algorithm for Online Exp-concave 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.