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

757 papers, page 15 of 16

701. NeurIPS 2026Robust Policy Optimization to Prevent Catastrophic Forgetting
702. NeurIPS 2026ROCKET: Rapid Optimization via Calibration-guided Knapsack-Enhanced Truncation for Efficient Model Compression
703. NeurIPS 2026RxnOptBench: Benchmarking LLMs for Reaction-Condition Optimization in Organic Methodology
704. NeurIPS 2026Sample complexity of stochastic optimization with integer variables
705. NeurIPS 2026Sample-Efficient Optimization over Generative Priors via Coarse Learnability
706. NeurIPS 2026SAS: Simple Attention Sparsification via End-to-End Optimization of Context Ranking
707. NeurIPS 2026Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits
708. NeurIPS 2026Scaling Optimization-Oriented Hypernetworks for Implicit Neural Representations
709. NeurIPS 2026Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization
710. NeurIPS 2026Select-then-differentiate: Solving Bilevel Optimization with Manifold Lower-level Solution Sets
711. NeurIPS 2026Self-Evolution Reasoner: Continuous Optimization via Policy-Intrinsic Exploration and Exploitation
712. NeurIPS 2026Sharper Guarantees for Misspecified Kernelized Bandit Optimization
713. NeurIPS 2026Sign-Based Optimizers Are Effective Under Heavy-Tailed Noise
714. NeurIPS 2026Signal-Adaptive Trust Regions for Gradient-Free Optimization of Recurrent Spiking Neural Networks
715. NeurIPS 2026Simple Extensions of Single-Objective Acquisition Functions and Hedge Strategies for Multi-Objective Bayesian Optimization
716. NeurIPS 2026Skill-Coupled Policy Optimization with Calibrated Group-Wise Advantage Estimation
717. NeurIPS 2026Skip the Hessian, Keep the Rates: Globalized Semismooth Newton with Lazy Hessian Updates
718. NeurIPS 2026Sliced Wasserstein Meets Quantum Optics: Provable Wavefunctions Tomography with Scarce Noisy Measurements
719. NeurIPS 2026SMOG: Scalable Meta-Learning for Multi-Objective Bayesian Optimization
720. NeurIPS 2026Solving Stochastic Control under Multiplicative and Internal Noise via Constrained Optimization
721. NeurIPS 2026SpecBlock: Block-Iterative Speculative Decoding with Dynamic Tree Drafting
722. NeurIPS 2026Spectral Annealing: Normalization-Path Exploration for Large-Scale Ising Optimization
723. NeurIPS 2026Stabilizing Policy Optimization via Logits Convexity
724. NeurIPS 2026Stable and Granular Policy Optimization for Generative Recommendation
725. NeurIPS 2026Stochastic Approximation Approach for Decentralized Optimization on Time Varying Random Networks
726. NeurIPS 2026Stochastic Dynamic Barrier Perturbed Gradient Methods for Nonconvex Simple Bilevel Optimization
727. NeurIPS 2026Stochastic Optimization with Random Search
728. NeurIPS 2026Stochastic Zeroth-Order Optimization Under Heavy-Tailed Noise
729. NeurIPS 2026Structure vs. Chaos: Asymmetric Entropic Optimization for Enforcing Instruction Hierarchy
730. NeurIPS 2026SWE-Pro: A Benchmark for Evaluating LLMs on Performance-Oriented Repository-Level Optimization
731. NeurIPS 2026TagBO: LLM-Driven Task-Aware Graph Bayesian Optimization for Scientific Discovery
732. NeurIPS 2026Take It or Leave It: Intent-Controlled Partial Optimal Transport
733. NeurIPS 2026Taming the Tails: Why Distributionally Robust Optimization Needs New Theory for Imbalanced Regression
734. NeurIPS 2026TEMPO: Temporal Enforcement via Mode-Separated Policy Optimization for Trustworthy LLM Backtesting
735. NeurIPS 2026TGPO: Temporal Grounded Policy Optimization for Signal Temporal Logic Tasks
736. NeurIPS 2026The Denoising Wrapper: A Modular Post-Processing Framework for Noisy First-Order Optimizers
737. NeurIPS 2026The Hidden Power of Scaling Factor in LoRA Optimization
738. NeurIPS 2026The Optimization Prior: Instilling depth for shallow networks, detail for coarse networks
739. NeurIPS 2026Tight Generalization Bounds for Noiseless Inverse Optimization
740. NeurIPS 2026Towards Convergence of PPO: An Approximate Descent Approach
741. NeurIPS 2026Towards Hyperparameter Transfer for Differentially Private Optimization
742. NeurIPS 2026Towards Settling the Complexity of Non-Euclidean Parallel Convex Optimization
743. NeurIPS 2026TPO: Tri-level Distributionally Robust Learning for OOD Direct Preference Optimization
744. NeurIPS 2026Training Optimal Large Diffusion Language Models
745. NeurIPS 2026Tree-Ensemble Repair through Constrained Optimization
746. NeurIPS 2026TROPT: An Open Framework for Unifying and Advancing Discrete Text Optimization
747. NeurIPS 2026Truncated Riemannian (1+1)-ES for Black-Box Optimization with Intrinsic Dimension Guarantees
748. NeurIPS 2026UECO: A Unified Encoder with Structure-Aware Attention Mixture via Iterative Edge Evolving for Neural Combinatorial Optimization
749. NeurIPS 2026Unifying Sparsity and Discreteness: One-Shot Pruning for Quantized LLMs via Discrete Optimization
750. NeurIPS 2026Universal Adaptive Proximal Gradient Methods via Gradient Mapping Accumulation

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.