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

958 papers, page 9 of 20

401. NeurIPS 2025MESS+: Dynamically Learned Inference-Time LLM Routing in Model Zoos with Service Level Guarantees
402. NeurIPS 2025Meta-Learning Objectives for Preference Optimization
403. NeurIPS 2025MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
404. NeurIPS 2025MGUP: A Momentum-Gradient Alignment Update Policy for Stochastic Optimization
405. NeurIPS 2025MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
406. NeurIPS 2025Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling
407. NeurIPS 2025MOBO-OSD: Batch Multi-Objective Bayesian Optimization via Orthogonal Search Directions
408. NeurIPS 2025Momentum-SAM: Sharpness Aware Minimization without Computational Overhead
409. NeurIPS 2025Multi-Expert Distributionally Robust Optimization for Out-of-Distribution Generalization
410. NeurIPS 2025Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms
411. NeurIPS 2025Multiplayer Federated Learning: Reaching Equilibrium with Less Communication
412. NeurIPS 2025Natural Gradient VI: Guarantees for Non-Conjugate Models
413. NeurIPS 2025Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference
414. NeurIPS 2025Neural Emulator Superiority: When Machine Learning for PDEs Surpasses its Training Data
415. NeurIPS 2025New Perspectives on the Polyak Stepsize: Surrogate Functions and Negative Results
416. NeurIPS 2025No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
417. NeurIPS 2025Non-convex entropic mean-field optimization via Best Response flow
418. NeurIPS 2025Non-Convex Tensor Recovery from Tube-Wise Sensing
419. NeurIPS 2025Non-monotone Submodular Optimization: $p$-Matchoid Constraints and Fully Dynamic Setting
420. NeurIPS 2025Non-Singularity of the Gradient Descent Map for Neural Networks with Piecewise Analytic Activations
421. NeurIPS 2025Non-stationary Bandit Convex Optimization: A Comprehensive Study
422. NeurIPS 2025Nonlinearly Preconditioned Gradient Methods: Momentum and Stochastic Analysis
423. NeurIPS 2025NopeRoomGS: Indoor 3D Gaussian Splatting Optimization without Camera Pose Input
424. NeurIPS 2025Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies
425. NeurIPS 2025Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
426. NeurIPS 2025OMiSO: Adaptive optimization of state-dependent brain stimulation to shape neural population states
427. NeurIPS 2025Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimization
428. NeurIPS 2025On Efficiency-Effectiveness Trade-off of Diffusion-based Recommenders
429. NeurIPS 2025On Extending Direct Preference Optimization to Accommodate Ties
430. NeurIPS 2025On the $O(\frac{\sqrt{d}}{K^{1/4}})$ Convergence Rate of AdamW Measured by $\ell_1$ Norm
431. NeurIPS 2025On the Complexity of Finding Stationary Points in Nonconvex Simple Bilevel Optimization
432. NeurIPS 2025On the Convergence of Single-Timescale Actor-Critic
433. NeurIPS 2025On the Convergence of Stochastic Smoothed Multi-Level Compositional Gradient Descent Ascent
434. NeurIPS 2025On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization
435. NeurIPS 2025On the Sample Complexity Bounds of Bilevel Reinforcement Learning
436. NeurIPS 2025On Traceability in $\ell_p$ Stochastic Convex Optimization
437. NeurIPS 2025Online Optimization for Offline Safe Reinforcement Learning
438. NeurIPS 2025Online Strategic Classification With Noise and Partial Feedback
439. NeurIPS 2025Optimistic Online-to-Batch Conversions for Accelerated Convergence and Universality
440. NeurIPS 2025PALQO: Physics-informed model for Accelerating Large-scale Quantum Optimization
441. NeurIPS 2025Partial Correlation Network Estimation by Semismooth Newton Methods
442. NeurIPS 2025Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
443. NeurIPS 2025PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs
444. NeurIPS 2025PDPO: Parametric Density Path Optimization
445. NeurIPS 2025Per-Architecture Training-Free Metric Optimization for Neural Architecture Search
446. NeurIPS 2025PhySense: Sensor Placement Optimization for Accurate Physics Sensing
447. NeurIPS 2025Preference Optimization by Estimating the Ratio of the Data Distribution
448. NeurIPS 2025Preference-Guided Diffusion for Multi-Objective Offline Optimization
449. NeurIPS 2025Preserving LLM Capabilities through Calibration Data Curation: From Analysis to Optimization
450. NeurIPS 2025PRESTO: Preimage-Informed Instruction Optimization for Prompting Black-Box LLMs

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.