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

560 papers, page 11 of 12

501. NeurIPS 2024Second-order forward-mode optimization of recurrent neural networks for neuroscience
502. NeurIPS 2024Semidefinite Relaxations of the Gromov-Wasserstein Distance
503. NeurIPS 2024SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization
504. NeurIPS 2024Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
505. NeurIPS 2024Sharpness-Aware Minimization Activates the Interactive Teaching's Understanding and Optimization
506. NeurIPS 2024Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance
507. NeurIPS 2024Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization
508. NeurIPS 2024Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions
509. NeurIPS 2024Sketching for Distributed Deep Learning: A Sharper Analysis
510. NeurIPS 2024SkipPredict: When to Invest in Predictions for Scheduling
511. NeurIPS 2024SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization
512. NeurIPS 2024SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
513. NeurIPS 2024Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation
514. NeurIPS 2024Stabilized Proximal-Point Methods for Federated Optimization
515. NeurIPS 2024Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm
516. NeurIPS 2024Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements
517. NeurIPS 2024Stochastic Newton Proximal Extragradient Method
518. NeurIPS 2024Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data
519. NeurIPS 2024Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss
520. NeurIPS 2024Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
521. NeurIPS 2024Stopping Bayesian Optimization with Probabilistic Regret Bounds
522. NeurIPS 2024Super Consistency of Neural Network Landscapes and Learning Rate Transfer
523. NeurIPS 2024SymILO: A Symmetry-Aware Learning Framework for Integer Linear Optimization
524. NeurIPS 2024Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization
525. NeurIPS 2024The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
526. NeurIPS 2024The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
527. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
528. NeurIPS 2024The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
529. NeurIPS 2024The Implicit Bias of Adam on Separable Data
530. NeurIPS 2024The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
531. NeurIPS 2024The Power of Extrapolation in Federated Learning
532. NeurIPS 2024The Road Less Scheduled
533. NeurIPS 2024The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
534. NeurIPS 2024The Space Complexity of Approximating Logistic Loss
535. NeurIPS 2024The Star Geometry of Critic-Based Regularizer Learning
536. NeurIPS 2024Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks
537. NeurIPS 2024There is No Silver Bullet: Benchmarking Methods in Predictive Combinatorial Optimization
538. NeurIPS 2024This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
539. NeurIPS 2024Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
540. NeurIPS 2024Topological obstruction to the training of shallow ReLU neural networks
541. NeurIPS 2024Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models
542. NeurIPS 2024Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression
543. NeurIPS 2024Transition Constrained Bayesian Optimization via Markov Decision Processes
544. NeurIPS 2024TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
545. NeurIPS 2024UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
546. NeurIPS 2024Universal Neural Functionals
547. NeurIPS 2024Universal Online Convex Optimization with $1$ Projection per Round
548. NeurIPS 2024Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
549. NeurIPS 2024Unraveling the Gradient Descent Dynamics of Transformers
550. NeurIPS 2024Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization

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.