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

2,330 papers, page 13 of 47

601. NeurIPS 2026Hawkeye: Hardware-Aware GPU Kernel Optimization with Minimal Supervision
602. NeurIPS 2026How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis
603. NeurIPS 2026Improved Regret Analysis For Parallel Gaussian Process Bandit Optimization
604. NeurIPS 2026Improving Quantized Zeroth-Order Optimization through Reconstructed Low-Rank Structures
605. NeurIPS 2026Improving the Optimization Landscape of Matrix Completion with $\epsilon$-close Surrogates
606. NeurIPS 2026In-Context Black-Box Optimization with Unreliable Feedback
607. NeurIPS 2026In-Expectation Convergence of Stochastic Gradient Methods under Heavy-Tailed Noise
608. NeurIPS 2026InQuant: In-Place Mixed-Precision KV Cache Quantization via Saliency-Aware Neighbor-Slot Reuse
609. NeurIPS 2026Instance-Dependent Bandit Convex Optimization in One Dimension
610. NeurIPS 2026Interpreting Neural Combinatorial Optimization via Evolving Programmatic Bottlenecks
611. NeurIPS 2026Intrinsic Muon: Spectral Optimization on Riemannian Matrix Manifolds
612. NeurIPS 2026Jacobian Descent for Multi-Objective Optimization
613. NeurIPS 2026Joint Optimization of Tool Creation and Use for Large Language Model Agents
614. NeurIPS 2026Kernel-based guarantees for nonlinear parametric models in Bayesian optimization
615. NeurIPS 2026KnowEvo: Knowledge Evolution for Protein Optimization
616. NeurIPS 2026Last-Iterate Convergence of Single-Loop Stochastic Methods for Constrained Convex-Concave Minimax Problems
617. NeurIPS 2026Layer Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant
618. NeurIPS 2026LDPCache: Locally Differentially Private Multi-Query Processing with Cache Optimization for Large Language Models
619. NeurIPS 2026Learning Minimal Sufficient Evidence Graphs for GraphRAG via Nash-Guided Optimization
620. NeurIPS 2026Learning Polyhedral Conformal Sets for Robust Optimization
621. NeurIPS 2026Learning Rate Decay Can Exponentially Accelerate SGD for Global Optimization of Nonconvex Functions
622. NeurIPS 2026Learning to Search, Searching to Learn: A Closed-Loop Framework for Large-Scale Vehicle Routing
623. NeurIPS 2026Learning When to Think: Dual-Reference Offline Optimization for Adaptive VLM Reasoning
624. NeurIPS 2026Likelihood-Free Generative Policy Optimization
625. NeurIPS 2026Literati: Towards Anytime Optimal Shape Generalized Trees via AO*
626. NeurIPS 2026Locally-Additive Regret for Delayed Non-stationary Bandit Convex Optimization
627. NeurIPS 2026LOCU: Löwdin-Orthogonalized Constraint Updates for Multi-Constraint Policy Optimization
628. NeurIPS 2026LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging
629. NeurIPS 2026LOTION: Smoothing the Optimization Landscape for Quantized Training
630. NeurIPS 2026MACRO: Training-free Multi-plane Attention for Closeup Render Optimization
631. NeurIPS 2026Manifold Drift in Flow Preference Optimization: A Root Cause of Reward Hacking
632. NeurIPS 2026MaPPO: Maximum a Posteriori Preference Optimization with Prior Knowledge
633. NeurIPS 2026Masked Sobolev Training for Feasibility-Reliable Optimization Proxies
634. NeurIPS 2026Match the Geometry, Skip the Surrogate: Extreme Low-Budget Optimization in High Dimensions
635. NeurIPS 2026Median-of-Means under Structured Heavy-Tailed Noise: High-Probability Bounds for Clipped Stochastic Optimization
636. NeurIPS 2026Minimax Optimization without Spurious Solutions in Optimal Transport Learning
637. NeurIPS 2026Mirror Descent-Ascent for mean-field min-max problems
638. NeurIPS 2026Mitigating Data Heterogeneity Effect in Client-Reshuffling-Based Federated Learning
639. NeurIPS 2026Mix-Opt: Mixed Optimization for Memory-Efficient Personalization of Text-to-Image Diffusion Models
640. NeurIPS 2026MM-OptBench: A Solver-Grounded Benchmark for Multimodal Optimization Modeling
641. NeurIPS 2026MOBO-CAPS: Multi-objective Bayesian Optimization with Cardinality-Aware Pareto Selection
642. NeurIPS 2026Mode-Controlled Policy Optimization: A Geometry-Aware Recipe for LLM Post-Training
643. NeurIPS 2026Module-Aware Optimization for Graph Neural Networks
644. NeurIPS 2026MoMHa: Multi-Objective Optimization of LLM Harnesses over Accuracy, Safety, and Tokens
645. NeurIPS 2026Multi-Nonsmooth-Nonconvex-Objective Optimization
646. NeurIPS 2026Nerve-Skeleton Message Passing for Federated Optimization with Overlapping Parameters
647. NeurIPS 2026Never Go Full Batch: Stochastic TMLE for Large-Scale Debiased Inference
648. NeurIPS 2026NLD4CO: Neural Langevin Dynamics for Combinatorial Optimization
649. NeurIPS 2026Nonconvex Decentralized Stochastic Bilevel Optimization under Heavy-Tailed Noise
650. NeurIPS 2026Offline Materials Optimization with CliqueFlowmer

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.