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 7 of 16

301. ICML 2026DREAM: Dual-Standard Semantic Homogeneity with Dynamic Optimization for Graph Learning with Label Noise
302. ICML 2026Dual Quaternion SE(3) Synchronization with Recovery Guarantees
303. ICML 2026Dynamic Symmetric Point Tracking: Tackling Non-ideal Reference in Analog In-memory Training
304. ICML 2026ECCO: Evidence-Driven Causal Reasoning for Compiler Optimization
305. ICML 2026Efficient Diffusion Models under Nonconvex Equality and Inequality constraints via Landing
306. ICML 2026Efficient Diffusion Models via Time Step Optimization with Consistent Training and Inference Constraints
307. ICML 2026Efficient Distributionally Robust Assortment Optimization in MNL Bandits
308. ICML 2026Eliminating Solution Bias in Differentially Private Optimization
309. ICML 2026Evolution of Benchmark: Black-Box Optimization Benchmark Design through Large Language Model
310. ICML 2026Exploiting weight-space symmetries for approximating curvature
311. ICML 2026FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs
312. ICML 2026Failure-Driven Workflow Refinement
313. ICML 2026Fast Spectrally Sparse Signal Reconstruction via Jacobi-Preconditioned Gradient Descent
314. ICML 2026FedCDWA: Decoupled Federated Prototype Distillation with Hierarchical Wasserstein Aggregation
315. ICML 2026Federated Bilevel Performative Prediction
316. ICML 2026FIBER: A Differentially Private Optimizer with Filter-Aware Innovation Bias Correction
317. ICML 2026Finding Stationary Points by Comparisons
318. ICML 2026Finite-time Convergence Analysis of Actor-Critic with Evolving Reward
319. ICML 2026Flat Minima and Generalization: Insights from Stochastic Convex Optimization
320. ICML 2026Flatland: The Adventures of Gradient Descent with Large Step Sizes
321. ICML 2026Flatness-Aware Stochastic Gradient Langevin Dynamics
322. ICML 2026FOAM: Frequency and Operator-Error Based Adaptive Damping Method for Reducing Staleness-Oriented Error for Shampoo
323. ICML 2026From Lyapunov Analysis to Algorithm Design in two-sided PL Minimax Optimization
324. ICML 2026From Muon to Gluon: Bridging Theory and Practice of LMO-based Optimizers for LLMs
325. ICML 2026From Optimization to Generalization under Heavy-Tailed Data: The Role of Gradient Clipping
326. ICML 2026Generative Large Neighborhood Search: Scalable Set Cover Optimization via Discrete Diffusion
327. ICML 2026Geometric Convergence of Gauss–Newton for Neural Networks: Riemannian Geometry and Adaptive Damping
328. ICML 2026Geometry-Misalignment in Distributional Learning
329. ICML 2026GIPO: Gaussian Importance Sampling Policy Optimization
330. ICML 2026GIST: Targeted Data Selection for Instruction Tuning via Coupled Optimization Geometry
331. ICML 2026Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation
332. ICML 2026Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
333. ICML 2026Gradient Flow Sampler-based Distributionally Robust Optimization
334. ICML 2026Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization
335. ICML 2026Gradient Testing and Estimation by Comparisons
336. ICML 2026Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity
337. ICML 2026GradPower: Powering Gradients for Faster Language Model Pre-Training
338. ICML 2026GRPO is Secretly a Process Reward Model
339. ICML 2026Hierarchical Decision Making with Structured Policies: A Principled Design via Inverse Optimization
340. ICML 2026High-Probability Convergence Guarantees of Decentralized SGD
341. ICML 2026HO-SFL: Hybrid-Order Split Federated Learning with Backprop-Free Clients and Dimension-Free Aggregation
342. ICML 2026Hom-PGD$^+$: Fast Reparameterized Optimization over Non-convex Ball-Homeomorphic Set
343. ICML 2026HONet: Data-Efficient Learning for Exact Cover Tasks via Hypergraph Optimization
344. ICML 2026How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models
345. ICML 2026Improved Convergence Analysis of Topology Dependence in Decentralized SGD
346. ICML 2026Improved Dimension Dependence for Bandit Convex Optimization with Gradient Variation
347. ICML 2026Improved Stochastic Optimization of LogSumExp
348. ICML 2026Improving Explicit Dynamic Gaussian Splatting Optimization via Update Mixture
349. ICML 2026In-Context Learning as Rate–Distortion Optimization
350. ICML 2026Incremental Learning of Sparse Attention Patterns in Transformers

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.