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

177 papers, page 3 of 4

101. ICLR 2025Nesterov acceleration in benignly non-convex landscapes
102. ICLR 2025Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
103. ICLR 2025Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization
104. ICLR 2025Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
105. ICLR 2025No Preference Left Behind: Group Distributional Preference Optimization
106. ICLR 2025Non-Equilibrium Dynamics of Hybrid Continuous-Discrete Ground-State Sampling
107. ICLR 2025Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
108. ICLR 2025Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
109. ICLR 2025Nonlinear Sequence Embedding by Monotone Variational Inequality
110. ICLR 2025Offline Hierarchical Reinforcement Learning via Inverse Optimization
111. ICLR 2025Offline Model-Based Optimization by Learning to Rank
112. ICLR 2025On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime
113. ICLR 2025On the Almost Sure Convergence of the Stochastic Three Points Algorithm
114. ICLR 2025On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
115. ICLR 2025On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models
116. ICLR 2025OPTAMI: Global Superlinear Convergence of High-order Methods
117. ICLR 2025Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
118. ICLR 2025Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
119. ICLR 2025Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
120. ICLR 2025Optimizing importance weighting in the presence of sub-population shifts
121. ICLR 2025Optimizing Neural Network Representations of Boolean Networks
122. ICLR 2025Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
123. ICLR 2025Overcoming Lower-Level Constraints in Bilevel Optimization: A Novel Approach with Regularized Gap Functions
124. ICLR 2025PABBO: Preferential Amortized Black-Box Optimization
125. ICLR 2025Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization
126. ICLR 2025Pareto Prompt Optimization
127. ICLR 2025ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization
128. ICLR 2025Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
129. ICLR 2025PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
130. ICLR 2025Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
131. ICLR 2025Problem-Parameter-Free Federated Learning
132. ICLR 2025Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization
133. ICLR 2025Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
134. ICLR 2025qNBO: quasi-Newton Meets Bilevel Optimization
135. ICLR 2025RainbowPO: A Unified Framework for Combining Improvements in Preference Optimization
136. ICLR 2025Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
137. ICLR 2025Revisiting Large-Scale Non-convex Distributionally Robust Optimization
138. ICLR 2025Revisiting Zeroth-Order Optimization: Minimum-Variance Two-Point Estimators and Directionally Aligned Perturbations
139. ICLR 2025Robustness of Quantum Algorithms for Nonconvex Optimization
140. ICLR 2025Scalable Decentralized Learning with Teleportation
141. ICLR 2025Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics
142. ICLR 2025Searching for Optimal Solutions with LLMs via Bayesian Optimization
143. ICLR 2025Second-Order Min-Max Optimization with Lazy Hessians
144. ICLR 2025Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning
145. ICLR 2025Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
146. ICLR 2025Sharpness-Aware Black-Box Optimization
147. ICLR 2025Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees
148. ICLR 2025SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization
149. ICLR 2025SOREL: A Stochastic Algorithm for Spectral Risks Minimization
150. ICLR 2025Standard Gaussian Process is All You Need for High-Dimensional Bayesian 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.