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

160 papers, page 3 of 4

101. ICML 2024On Discrete Prompt Optimization for Diffusion Models
102. ICML 2024On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization
103. ICML 2024On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
104. ICML 2024On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
105. ICML 2024On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
106. ICML 2024On the Last-Iterate Convergence of Shuffling Gradient Methods
107. ICML 2024Optimal Differentially Private Model Training with Public Data
108. ICML 2024Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
109. ICML 2024Optimization without Retraction on the Random Generalized Stiefel Manifold
110. ICML 2024Overcoming the Optimizer's Curse: Obtaining Realistic Prescriptions from Neural Networks
111. ICML 2024Plug-in Performative Optimization
112. ICML 2024Position: Leverage Foundational Models for Black-Box Optimization
113. ICML 2024Position: Optimization in SciML Should Employ the Function Space Geometry
114. ICML 2024Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
115. ICML 2024Principled Preferential Bayesian Optimization
116. ICML 2024Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
117. ICML 2024Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
118. ICML 2024Proactive DP: A Multiple Target Optimization Framework for DP-SGD
119. ICML 2024Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization
120. ICML 2024Projection-Free Online Convex Optimization with Time-Varying Constraints
121. ICML 2024Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
122. ICML 2024Quantum Algorithm for Online Exp-concave Optimization
123. ICML 2024Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
124. ICML 2024Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
125. ICML 2024Random Scaling and Momentum for Non-smooth Non-convex Optimization
126. ICML 2024Rate-Optimal Policy Optimization for Linear Markov Decision Processes
127. ICML 2024Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
128. ICML 2024Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
129. ICML 2024Reflective Policy Optimization
130. ICML 2024Rethinking Optimization and Architecture for Tiny Language Models
131. ICML 2024Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
132. ICML 2024Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences
133. ICML 2024Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient
134. ICML 2024Robust Data-driven Prescriptiveness Optimization
135. ICML 2024Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space
136. ICML 2024Robustly Learning Single-Index Models via Alignment Sharpness
137. ICML 2024Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
138. ICML 2024Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
139. ICML 2024Simplicity Bias via Global Convergence of Sharpness Minimization
140. ICML 2024Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
141. ICML 2024Small-loss Adaptive Regret for Online Convex Optimization
142. ICML 2024Smooth Tchebycheff Scalarization for Multi-Objective Optimization
143. ICML 2024Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence
144. ICML 2024SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
145. ICML 2024Stochastic Optimization with Arbitrary Recurrent Data Sampling
146. ICML 2024Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
147. ICML 2024Symmetric Matrix Completion with ReLU Sampling
148. ICML 2024Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
149. ICML 2024Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
150. ICML 2024Token-level Direct Preference 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.