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

541 papers, page 7 of 11

301. ICLR 2025Overcoming Lower-Level Constraints in Bilevel Optimization: A Novel Approach with Regularized Gap Functions
302. ICLR 2025PABBO: Preferential Amortized Black-Box Optimization
303. ICLR 2025Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization
304. ICLR 2025Pareto Prompt Optimization
305. ICLR 2025ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization
306. ICLR 2025Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
307. ICLR 2025PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
308. ICLR 2025Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
309. ICLR 2025Problem-Parameter-Free Federated Learning
310. ICLR 2025Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization
311. ICLR 2025Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
312. ICLR 2025qNBO: quasi-Newton Meets Bilevel Optimization
313. ICLR 2025RainbowPO: A Unified Framework for Combining Improvements in Preference Optimization
314. ICLR 2025Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
315. ICLR 2025Revisiting Large-Scale Non-convex Distributionally Robust Optimization
316. ICLR 2025Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
317. ICLR 2025Robustness of Quantum Algorithms for Nonconvex Optimization
318. ICLR 2025Scalable Decentralized Learning with Teleportation
319. ICLR 2025Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics
320. ICLR 2025Searching for Optimal Solutions with LLMs via Bayesian Optimization
321. ICLR 2025Second-Order Min-Max Optimization with Lazy Hessians
322. ICLR 2025Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
323. ICLR 2025Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
324. ICLR 2025Sharpness-Aware Black-Box Optimization
325. ICLR 2025Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees
326. ICLR 2025SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization
327. ICLR 2025SOREL: A Stochastic Algorithm for Spectral Risks Minimization
328. ICLR 2025Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
329. ICLR 2025Stochastic Polyak Step-sizes and Momentum: Convergence Guarantees and Practical Performance
330. ICLR 2025Taming Transformer Without Using Learning Rate Warmup
331. ICLR 2025Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster
332. ICLR 2025The AdEMAMix Optimizer: Better, Faster, Older
333. ICLR 2025The Crucial Role of Samplers in Online Direct Preference Optimization
334. ICLR 2025The Directionality of Optimization Trajectories in Neural Networks
335. ICLR 2025The Optimization Landscape of SGD Across the Feature Learning Strength
336. ICLR 2025Tight Lower Bounds under Asymmetric High-Order Hölder Smoothness and Uniform Convexity
337. ICLR 2025Tight Time Complexities in Parallel Stochastic Optimization with Arbitrary Computation Dynamics
338. ICLR 2025TIS-DPO: Token-level Importance Sampling for Direct Preference Optimization With Estimated Weights
339. ICLR 2025To Clip or not to Clip: the Dynamics of SGD with Gradient Clipping in High-Dimensions
340. ICLR 2025TopoGaussian: Inferring Internal Topology Structures from Visual Clues
341. ICLR 2025Towards Faster Decentralized Stochastic Optimization with Communication Compression
342. ICLR 2025Towards hyperparameter-free optimization with differential privacy
343. ICLR 2025Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
344. ICLR 2025Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization
345. ICLR 2025Tuning-Free Bilevel Optimization: New Algorithms and Convergence Analysis
346. ICLR 2025Understanding Optimization in Deep Learning with Central Flows
347. ICLR 2025UniCBE: An Uniformity-driven Comparing Based Evaluation Framework with Unified Multi-Objective Optimization
348. ICLR 2025Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization
349. ICLR 2025Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
350. ICLR 2025UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning

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.