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 43 of 47

2101. ICML 2023Constrained Efficient Global Optimization of Expensive Black-box Functions
2102. ICML 2023Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
2103. ICML 2023Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data
2104. ICML 2023Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss
2105. ICML 2023Cut your Losses with Squentropy
2106. ICML 2023Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
2107. ICML 2023DADAO: Decoupled Accelerated Decentralized Asynchronous Optimization
2108. ICML 2023Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity
2109. ICML 2023Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit Feedback
2110. ICML 2023DIFF2: Differential Private Optimization via Gradient Differences for Nonconvex Distributed Learning
2111. ICML 2023Differentially Private Stochastic Convex Optimization under a Quantile Loss Function
2112. ICML 2023Diffusion Models for Black-Box Optimization
2113. ICML 2023Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost
2114. ICML 2023DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
2115. ICML 2023Dynamic Constrained Submodular Optimization with Polylogarithmic Update Time
2116. ICML 2023EF21-P and Friends: Improved Theoretical Communication Complexity for Distributed Optimization with Bidirectional Compression
2117. ICML 2023Efficient displacement convex optimization with particle gradient descent
2118. ICML 2023Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization
2119. ICML 2023End-to-End Learning for Stochastic Optimization: A Bayesian Perspective
2120. ICML 2023Escaping saddle points in zeroth-order optimization: the power of two-point estimators
2121. ICML 2023Fast as CHITA: Neural Network Pruning with Combinatorial Optimization
2122. ICML 2023Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
2123. ICML 2023Faster Rates of Convergence to Stationary Points in Differentially Private Optimization
2124. ICML 2023Federated Online and Bandit Convex Optimization
2125. ICML 2023FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization
2126. ICML 2023Generalized Polyak Step Size for First Order Optimization with Momentum
2127. ICML 2023Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization
2128. ICML 2023Generative Pretraining for Black-Box Optimization
2129. ICML 2023Global Optimization with Parametric Function Approximation
2130. ICML 2023Graph Reinforcement Learning for Network Control via Bi-Level Optimization
2131. ICML 2023High Probability Convergence of Stochastic Gradient Methods
2132. ICML 2023High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance
2133. ICML 2023Implicit Jacobian regularization weighted with impurity of probability output
2134. ICML 2023Improving Bi-level Optimization Based Methods with Inspiration from Humans' Classroom Study Techniques
2135. ICML 2023Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
2136. ICML 2023Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement
2137. ICML 2023Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach
2138. ICML 2023Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability
2139. ICML 2023Low Complexity Homeomorphic Projection to Ensure Neural-Network Solution Feasibility for Optimization over (Non-)Convex Set
2140. ICML 2023Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions
2141. ICML 2023Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime
2142. ICML 2023Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization
2143. ICML 2023Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods
2144. ICML 2023Nonparametric Iterative Machine Teaching
2145. ICML 2023Omnipredictors for Constrained Optimization
2146. ICML 2023On the Convergence of Federated Averaging with Cyclic Client Participation
2147. ICML 2023On the Convergence of SARSA with Linear Function Approximation
2148. ICML 2023On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm
2149. ICML 2023On the Convergence Rate of Gaussianization with Random Rotations
2150. ICML 2023On User-Level Private Convex 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.