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

2,330 papers, page 40 of 47

1951. NeurIPS 2024The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof
1952. NeurIPS 2024The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
1953. NeurIPS 2024The Implicit Bias of Adam on Separable Data
1954. NeurIPS 2024The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
1955. NeurIPS 2024The Power of Extrapolation in Federated Learning
1956. NeurIPS 2024The Road Less Scheduled
1957. NeurIPS 2024The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
1958. NeurIPS 2024The Space Complexity of Approximating Logistic Loss
1959. NeurIPS 2024The Star Geometry of Critic-Based Regularizer Learning
1960. NeurIPS 2024Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks
1961. NeurIPS 2024There is No Silver Bullet: Benchmarking Methods in Predictive Combinatorial Optimization
1962. NeurIPS 2024This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
1963. NeurIPS 2024Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
1964. NeurIPS 2024Topological obstruction to the training of shallow ReLU neural networks
1965. NeurIPS 2024Toward Global Convergence of Gradient EM for Over-Paramterized Gaussian Mixture Models
1966. NeurIPS 2024Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression
1967. NeurIPS 2024Transition Constrained Bayesian Optimization via Markov Decision Processes
1968. NeurIPS 2024TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
1969. NeurIPS 2024UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
1970. NeurIPS 2024Universal Neural Functionals
1971. NeurIPS 2024Universal Online Convex Optimization with $1$ Projection per Round
1972. NeurIPS 2024Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
1973. NeurIPS 2024Unraveling the Gradient Descent Dynamics of Transformers
1974. NeurIPS 2024Unveil Benign Overfitting for Transformer in Vision: Training Dynamics, Convergence, and Generalization
1975. NeurIPS 2024UQ-Guided Hyperparameter Optimization for Iterative Learners
1976. NeurIPS 2024UQE: A Query Engine for Unstructured Databases
1977. NeurIPS 2024Variational Delayed Policy Optimization
1978. NeurIPS 2024Warm-starting Push-Relabel
1979. NeurIPS 2024Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
1980. NeurIPS 2024Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness
1981. NeurIPS 2024Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
1982. NeurIPS 2024Why Do We Need Weight Decay in Modern Deep Learning?
1983. NeurIPS 2024Why Transformers Need Adam: A Hessian Perspective
1984. NeurIPS 2024Why Warmup the Learning Rate? Underlying Mechanisms and Improvements
1985. CVPR 2023Attribute-Preserving Face Dataset Anonymization via Latent Code Optimization
1986. CVPR 2023Cross-Guided Optimization of Radiance Fields With Multi-View Image Super-Resolution for High-Resolution Novel View Synthesis
1987. CVPR 2023Deep Dive Into Gradients: Better Optimization for 3D Object Detection With Gradient-Corrected IoU Supervision
1988. CVPR 2023DeepMapping2: Self-Supervised Large-Scale LiDAR Map Optimization
1989. CVPR 2023Elastic Aggregation for Federated Optimization
1990. CVPR 2023GradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency
1991. CVPR 2023High-Fidelity 3D GAN Inversion by Pseudo-Multi-View Optimization
1992. CVPR 2023LiDAR-in-the-Loop Hyperparameter Optimization
1993. CVPR 2023Optimization-Inspired Cross-Attention Transformer for Compressive Sensing
1994. CVPR 2023PyPose: A Library for Robot Learning With Physics-Based Optimization
1995. CVPR 2023Robust Generalization Against Photon-Limited Corruptions via Worst-Case Sharpness Minimization
1996. CVPR 2023StyleGAN Salon: Multi-View Latent Optimization for Pose-Invariant Hairstyle Transfer
1997. CVPR 2023Towards Better Decision Forests: Forest Alternating Optimization
1998. CVPR 2023Transformer-Based Learned Optimization
1999. CVPR 2023Tunable Convolutions With Parametric Multi-Loss Optimization
2000. ICLR 2023$\Lambda$-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells

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.