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

178 papers, page 3 of 4

101. ICLR 2026Mitigating Mismatch within Reference-based Preference Optimization
102. ICLR 2026Mitigating Spurious Correlation via Distributionally Robust Learning with Hierarchical Ambiguity Sets
103. ICLR 2026MuonBP: Faster Muon via Block-Periodic Orthogonalization
104. ICLR 2026Native Adaptive Solution Expansion for Diffusion-based Combinatorial Optimization
105. ICLR 2026Nesterov Finds GRAAL: Optimal and Adaptive Gradient Method for Convex Optimization
106. ICLR 2026NeuCLIP: Efficient Large-Scale CLIP Training with Neural Normalizer Optimization
107. ICLR 2026Newton Method Revisited: Global Convergence Rates up to $O(1/k^3)$ for Stepsize Schedules and Linesearch Procedures
108. ICLR 2026NI Sampling: Accelerating Discrete Diffusion Sampling by Token Order Optimization
109. ICLR 2026Non-Asymptotic Analysis of Efficiency in Conformalized Regression
110. ICLR 2026Non-Convex Federated Optimization under Cost-Aware Client Selection
111. ICLR 2026Obscure but Effective: Classical Chinese Jailbreak Prompt Optimization via Bio-Inspired Search
112. ICLR 2026Offline Preference-Based Value Optimization
113. ICLR 2026OFMU: OPTIMIZATION-DRIVEN FRAMEWORK FOR MACHINE UNLEARNING
114. ICLR 2026OmniPortrait: Fine-Grained Personalized Portrait Synthesis via Pivotal Optimization
115. ICLR 2026On Smoothness Bounds for Non-Clairvoyant Scheduling with Predictions
116. ICLR 2026On the $O(1/T)$ Convergence of Alternating Gradient Descent–Ascent in Bilinear Games
117. ICLR 2026On the Benefits of Weight Normalization for Overparameterized Matrix Sensing
118. ICLR 2026On the Convergence Behavior of Preconditioned Gradient Descent Toward the Rich Learning Regime
119. ICLR 2026On the Convergence Direction of Gradient Descent
120. ICLR 2026On the Convergence of Two-Layer Kolmogorov-Arnold Networks with First-Layer Training
121. ICLR 2026On The Surprising Effectiveness of a Single Global Merging in Decentralized Learning
122. ICLR 2026Online Black-Box Prompt Optimization with Regret Guarantees under Noisy Feedback
123. ICLR 2026Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards
124. ICLR 2026OptMerge: Unifying Multimodal LLM Capabilities and Modalities via Model Merging
125. ICLR 2026Overparametrization bends the landscape: BBP transitions at initialization in simple Neural Networks
126. ICLR 2026Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers
127. ICLR 2026Polynomial Convergence of Riemannian Diffusion Models
128. ICLR 2026Primal-Dual Policy Optimization for Adversarial Linear CMDPs
129. ICLR 2026Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction
130. ICLR 2026RADAR: Learning to Route with Asymmetry-aware Distance Representations
131. ICLR 2026Reducing Contextual Stochastic Bilevel Optimization via Structured Function Approximation
132. ICLR 2026ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization
133. ICLR 2026Reinforcement Unlearning via Group Relative Policy Optimization
134. ICLR 2026Relative Entropy Pathwise Policy Optimization
135. ICLR 2026Riemannian Federated Learning via Averaging Gradient Streams
136. ICLR 2026Riemannian Optimization on Relaxed Indicator Matrix Manifold
137. ICLR 2026Riemannian Zeroth-Order Gradient Estimation with Structure-Preserving Metrics for Geodesically Incomplete Manifolds
138. ICLR 2026Ringleader ASGD: The First Asynchronous SGD with Optimal Time Complexity under Data Heterogeneity
139. ICLR 2026RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training
140. ICLR 2026Robust Optimization for Mitigating Reward Hacking with Correlated Proxies
141. ICLR 2026Robust Preference Optimization: Aligning Language Models with Noisy Preference Feedback
142. ICLR 2026Scalable Second-order Riemannian Optimization for $K$-means Clustering
143. ICLR 2026Scaling Direct Feedback Learning with Theoretical Guarantees
144. ICLR 2026SCRAPL: Scattering Transform with Random Paths for Machine Learning
145. ICLR 2026Seesaw: Accelerating Training by Balancing Batch Size and Learning Rate Scheduling
146. ICLR 2026Semi-Supervised Preference Optimization with Limited Feedback
147. ICLR 2026Set Representation Auxiliary Learning with Adversarial Encoding Perturbation and Optimization
148. ICLR 2026Sign-SGD via Parameter-Free Optimization
149. ICLR 2026Single-Loop Byzantine-Resilient Federated Bilevel Optimization
150. ICLR 2026Single-stream Policy Optimization

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.