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 10 of 47

451. ICML 2026RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
452. ICML 2026Robust Bayesian Optimisation with Unbounded Corruptions
453. ICML 2026Robust Contextual Optimization with Missing Covariates
454. ICML 2026Robust Learning via Nested Distributionally Robust Optimization
455. ICML 2026Romberg-Extrapolated Zeroth-Order Gradient Estimator: Higher-Order Bias Reduction with Preserved Leading Directional Variance
456. ICML 2026Row-Stochastic Matrices Can Provably Outperform Doubly Stochastic Matrices in Decentralized Learning
457. ICML 2026SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling
458. ICML 2026Safeguarded Stochastic Polyak Step Sizes for Non-smooth Optimization: Robust Performance Without Small (Sub)Gradients
459. ICML 2026SALAAD: Sparse And Low-Rank Adaptation via ADMM for Large Language Model Inference
460. ICML 2026Scalable and Stable Estimation of Amari $\alpha$-Divergence using Random Fourier Features
461. ICML 2026Second-Order Bilevel Optimization with Accelerated Convergence Rates
462. ICML 2026Segment-Aligned Policy Optimization for Multi-Modal Reasoning
463. ICML 2026Sharpness-Aware Minimization Can Hallucinate Minimizers
464. ICML 2026SimpleGPT: Improving GPT via A Simple Normalization Strategy
465. ICML 2026Simultaneous Confidence Bounds for Aggregated Effects via Exact Subset Optimization
466. ICML 2026Singularity-aware Optimization via Randomized Geometric Probing: Towards Stable Non-smooth Optimization
467. ICML 2026SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
468. ICML 2026Softsign: Smooth Sign in Your Optimizer For Better Parameter Heterogeneity Handling
469. ICML 2026Solving Imperfect-Recall Games via Sum-of-Squares Optimization
470. ICML 2026Solving Stochastic Variational Inequalities without the Bounded Variance Assumption
471. ICML 2026Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel Optimization
472. ICML 2026Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training
473. ICML 2026Stability and Generalization of Nonconvex Optimization with Heavy-Tailed Noise
474. ICML 2026Step-Size Stability in Stochastic Optimization: A Theoretical Perspective
475. ICML 2026STLA: Spatiotemporal Lookahead Alignment for Post-Training Quantization
476. ICML 2026Stochastic Gradient Methods under Heavy-Tailed Noises in Weakly Convex Optimization
477. ICML 2026Submodular Optimization for Minimal Augmentation in Robust Language Model Alignment
478. ICML 2026Success-Conditioning as Policy Improvement: The Optimization Problem Solved by Imitating Success
479. ICML 2026Support-Proximity Augmented Diffusion Estimation for Offline Black-Box Optimization
480. ICML 2026Taking the GP Out of the Loop
481. ICML 2026Taming Stochastic Gradient Descent: Almost Sure Convergence and Saddle-Point Avoidance under $(L_{0},L_{1})$-Smoothness
482. ICML 2026Target-Aware Bandit Allocation for Scalable Surrogate Optimization in Chemical Space
483. ICML 2026The Differences Between Direct Alignment Algorithms are a Blur
484. ICML 2026The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
485. ICML 2026Theoretical Analysis of Sparse Optimization with Reparameterization, Weight Decay, and Adaptive Learning Rate
486. ICML 2026Theoretical Challenges in Learning for Branch-and-Cut
487. ICML 2026TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization
488. ICML 2026Tournament Style RL: Stabilizing Policy Optimization on Non Verifiable Problems
489. ICML 2026Towards Disentangled Preference Optimization Dynamics: Suppress the Loser, Preserve the Winner
490. ICML 2026Towards Fully Parameter-Free Stochastic Optimization: Grid Search with Self-Bounding Analysis
491. ICML 2026Towards Parameter-Free Temporal Difference Learning
492. ICML 2026Trainable Nonexpansive Denoisers for Contractive Image Reconstruction
493. ICML 2026Training Prompt Matters: State-Adaptive Optimization for Robust Fine-Tuning
494. ICML 2026Trajectory Stitching for Solving Inverse Problems with Flow-Based Models
495. ICML 2026TSP with Predictions: Heatmap to Tour with Provable Guarantees
496. ICML 2026TurboGS: Accelerating 3D Gaussian Splatting via Error-Guided Sparse Pixel Sampling and Optimization
497. ICML 2026Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
498. ICML 2026UCPO: Uncertainty-Aware Policy Optimization
499. ICML 2026Unbiased Principles, Robust Rewards
500. ICML 2026UniDrag: Unified Multi-Field Prediction and Robust Shape Optimization for Vehicle Aerodynamics

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.