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

736 papers, page 13 of 15

601. ICML 2024Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
602. ICML 2024Random Exploration in Bayesian Optimization: Order-Optimal Regret and Computational Efficiency
603. ICML 2024Random Scaling and Momentum for Non-smooth Non-convex Optimization
604. ICML 2024Rate-Optimal Policy Optimization for Linear Markov Decision Processes
605. ICML 2024Realistic Unsupervised CLIP Fine-tuning with Universal Entropy Optimization
606. ICML 2024Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
607. ICML 2024Reflective Policy Optimization
608. ICML 2024Rethinking Optimization and Architecture for Tiny Language Models
609. ICML 2024Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
610. ICML 2024Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences
611. ICML 2024Risk-Sensitive Policy Optimization via Predictive CVaR Policy Gradient
612. ICML 2024Robust Data-driven Prescriptiveness Optimization
613. ICML 2024Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space
614. ICML 2024Robustly Learning Single-Index Models via Alignment Sharpness
615. ICML 2024Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
616. ICML 2024Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
617. ICML 2024Simplicity Bias via Global Convergence of Sharpness Minimization
618. ICML 2024Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
619. ICML 2024Small-loss Adaptive Regret for Online Convex Optimization
620. ICML 2024Smooth Tchebycheff Scalarization for Multi-Objective Optimization
621. ICML 2024Smoothing Proximal Gradient Methods for Nonsmooth Sparsity Constrained Optimization: Optimality Conditions and Global Convergence
622. ICML 2024SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
623. ICML 2024Stochastic Optimization with Arbitrary Recurrent Data Sampling
624. ICML 2024Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
625. ICML 2024Symmetric Matrix Completion with ReLU Sampling
626. ICML 2024Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
627. ICML 2024Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More
628. ICML 2024Token-level Direct Preference Optimization
629. ICML 2024Towards Efficient Exact Optimization of Language Model Alignment
630. ICML 2024Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape
631. ICML 2024Tuning-Free Stochastic Optimization
632. ICML 2024Two Fists, One Heart: Multi-Objective Optimization Based Strategy Fusion for Long-tailed Learning
633. ICML 2024Two-timescale Derivative Free Optimization for Performative Prediction with Markovian Data
634. ICML 2024Universal Gradient Methods for Stochastic Convex Optimization
635. ICML 2024Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
636. ICML 2024Vanilla Bayesian Optimization Performs Great in High Dimensions
637. ICML 2024Verifying message-passing neural networks via topology-based bounds tightening
638. ICML 2024Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
639. ICML 2023A Distribution Optimization Framework for Confidence Bounds of Risk Measures
640. ICML 2023A Fully First-Order Method for Stochastic Bilevel Optimization
641. ICML 2023A Theoretical Analysis of the Learning Dynamics under Class Imbalance
642. ICML 2023Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
643. ICML 2023Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations
644. ICML 2023Accelerated Stochastic Optimization Methods under Quasar-convexity
645. ICML 2023Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift
646. ICML 2023Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation
647. ICML 2023Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimization
648. ICML 2023Automatically Auditing Large Language Models via Discrete Optimization
649. ICML 2023Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong Convexity
650. ICML 2023Bandit Online Linear Optimization with Hints and Queries

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.