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 9 of 16

401. ICML 2026Normalized Rewards for Preference Optimization
402. ICML 2026Not All Answers Are Contextually Persuadable: Inference Dynamics in Large Language Models under Contextual Influence
403. ICML 2026Off-Policy Learning in Large Action Spaces: Optimization Matters More Than Estimation
404. ICML 2026OLion: Approaching the Hadamard Ideal by Intersecting Spectral and L inf Implicit Biases
405. ICML 2026On Densest $k$-Subgraph Mining and Diagonal Loading: Optimization Landscape and Finite-Step Exact Convergence Analysis
406. ICML 2026On Regret Bounds of Thompson Sampling for Bayesian Optimization
407. ICML 2026On the Anisotropy of Score-Based Generative Models
408. ICML 2026On the Convergence of Decentralized Stochastic Minimax Optimization Algorithm with Compressed Communication
409. ICML 2026On the Convergence Rate of LoRA Gradient Descent
410. ICML 2026On the Optimization Trajectory of DeepWalk Embeddings
411. ICML 2026On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization
412. ICML 2026On the Role of Batch Size in Stochastic Conditional Gradient Methods
413. ICML 2026One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining
414. ICML 2026Operator Splitting with Hamilton-Jacobi-based Proximals
415. ICML 2026OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
416. ICML 2026Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verification
417. ICML 2026Optimal Anytime Algorithms for Online Convex Optimization with Adversarial Constraints
418. ICML 2026Optimal Regret for Policy Optimization in Contextual Bandits
419. ICML 2026Optimal Transport with Symmetry Groups
420. ICML 2026Optimal Transport–Guided Stochastic Control for Graph Combinatorial Optimization
421. ICML 2026OptMaster: A DAG-Based Framework for Formulation and Heuristic Discovery in Optimization
422. ICML 2026Parallel Stochastic Gradient-Based Planning for World Models
423. ICML 2026Parameter-Masked Decoupled Optimization for Cross-Domain Class-Incremental Learning
424. ICML 2026PASO: Step Parallel Stochastic Optimization
425. ICML 2026PepCompass: Navigating Peptide Embedding Spaces Using Riemannian Geometry
426. ICML 2026PICACO: Pluralistic In-Context Value Alignment via Total Correlation Optimization
427. ICML 2026Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes
428. ICML 2026Preconditioning Neural Tangent Kernel for Adaptive Optimization
429. ICML 2026Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction
430. ICML 2026Preference-Modulated Structural Attention for Multi-Objective Combinatorial Optimization
431. ICML 2026Probability of Matching for Batch Multi-Objective Bayesian Optimization
432. ICML 2026Projection-Free Algorithms for Minimax Problems
433. ICML 2026QUATRO: Query-Adaptive Trust Region Policy Optimization for LLM Fine-tuning
434. ICML 2026Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes
435. ICML 2026Ratio-Variance Regularized Policy Optimization
436. ICML 2026Recursive Monte-Carlo Tree Search
437. ICML 2026Reducing Per-Sample Harm in Stochastic Optimization
438. ICML 2026Reflect-then-Correct: Rebalancing Task Optimization for Generalizable Meta-Reinforcement Learning via Distributional Value Error Reduction
439. ICML 2026Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes
440. ICML 2026Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief
441. ICML 2026Reparameterization Flow Policy Optimization
442. ICML 2026Reparameterization Proximal Policy Optimization
443. ICML 2026Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models
444. ICML 2026Rethinking Convergence in MoE Training: The Role of Routing Sparsity
445. ICML 2026Rethinking Neural Network Learning Rates: A Stackelberg Perspective
446. ICML 2026Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games
447. ICML 2026Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens
448. ICML 2026Riemannian Dueling Optimization
449. ICML 2026Riemannian Optimization for Fair Spectral Clustering
450. ICML 2026Riemannian stochastic optimization for sufficient dimension reduction

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.