Deep learning · optimization papers, 2023–2026

Key findings

• Deep learning · optimization fell from 256 papers in 2023 to 240 in 2026, so interest is cooling.
• NeurIPS publishes the most Deep learning · optimization work: 500 papers from 2023 to 2026, 52% of the four-venue total.
• The fastest-growing overlap is with Alignment and Safety: papers tagged with both rose from 5 in 2023 to 23 in 2026.
• Among the 11 topics under Deep Learning, it ranks #6 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Achieving Directional-Stationarity from a Single Random Direction Step
• ICML 2026Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
• ICLR 2026From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
• CVPR 2026Coverage Optimization for Camera View Selection
• NeurIPS 2025High-Performance Arithmetic Circuit Optimization via Differentiable Architecture Search
• ICML 2025Feature-Mapping Topology Optimization with Neural Heaviside Signed Distance Functions
• ICLR 2025Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
• CVPR 2025HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition
• NeurIPS 2024$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
• ICML 2024Barrier Algorithms for Constrained Non-Convex Optimization
• ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
• CVPR 2024Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
• NeurIPS 2023$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning
• ICML 2023Buying Information for Stochastic Optimization
• ICLR 2023Alternating Differentiation for Optimization Layers
• CVPR 2023Visual-Language Prompt Tuning With Knowledge-Guided Context Optimization
• NeurIPS 2026Adaptive Conditional Gradient Sliding: Projection-Free and Line-Search-Free Acceleration
• ICML 2026Riemannian Optimization for Fair Spectral Clustering
• ICLR 2026Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective
• CVPR 2026Its Never Too Late Noise Optimization for Collapse Recovery in

All Deep learning · optimization papers

294 papers, page 1 of 6

1. CVPR 2024Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
2. ICLR 2024A Discretization Framework for Robust Contextual Stochastic Optimization
3. ICLR 2024A Precise Characterization of SGD Stability Using Loss Surface Geometry
4. ICLR 2024Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
5. ICLR 2024Accelerating Sinkhorn algorithm with sparse Newton iterations
6. ICLR 2024Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization
7. ICLR 2024Bayesian Coreset Optimization for Personalized Federated Learning
8. ICLR 2024Communication-Efficient Federated Non-Linear Bandit Optimization
9. ICLR 2024Constraint-Free Structure Learning with Smooth Acyclic Orientations
10. ICLR 2024Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
11. ICLR 2024Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
12. ICLR 2024Dropout Enhanced Bilevel Training
13. ICLR 2024Fast Equilibrium of SGD in Generic Situations
14. ICLR 2024FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
15. ICLR 2024Implicit Maximum a Posteriori Filtering via Adaptive Optimization
16. ICLR 2024Large Language Models to Enhance Bayesian Optimization
17. ICLR 2024Learning model uncertainty as variance-minimizing instance weights
18. ICLR 2024Linear attention is (maybe) all you need (to understand Transformer optimization)
19. ICLR 2024Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts
20. ICLR 2024Local Composite Saddle Point Optimization
21. ICLR 2024Magnitude Invariant Parametrizations Improve Hypernetwork Learning
22. ICLR 2024Most discriminative stimuli for functional cell type clustering
23. ICLR 2024Neur2RO: Neural Two-Stage Robust Optimization
24. ICLR 2024On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback
25. ICLR 2024On the Parameterization of Second-Order Optimization Effective towards the Infinite Width
26. ICLR 2024Optimistic Bayesian Optimization with Unknown Constraints
27. ICLR 2024Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
28. ICLR 2024Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
29. ICLR 2024Robust Model-Based Optimization for Challenging Fitness Landscapes
30. ICLR 2024Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
31. ICLR 2024Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization
32. ICML 2024A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
33. ICML 2024A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
34. ICML 2024A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
35. ICML 2024A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles
36. ICML 2024Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
37. ICML 2024Activation-Descent Regularization for Input Optimization of ReLU Networks
38. ICML 2024Advancing Dynamic Sparse Training by Exploring Optimization Opportunities
39. ICML 2024Autonomous Sparse Mean-CVaR Portfolio Optimization
40. ICML 2024Barrier Algorithms for Constrained Non-Convex Optimization
41. ICML 2024Bayesian Optimization of Function Networks with Partial Evaluations
42. ICML 2024Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints
43. ICML 2024Compact Optimality Verification for Optimization Proxies
44. ICML 2024Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
45. ICML 2024Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers
46. ICML 2024Delving into the Convergence of Generalized Smooth Minimax Optimization
47. ICML 2024Differentiable Distributionally Robust Optimization Layers
48. ICML 2024Differentiable Mapper for Topological Optimization of Data Representation
49. ICML 2024Distributed Bilevel Optimization with Communication Compression
50. ICML 2024Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification

FAQ

How many Deep learning · optimization papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

953 in total: 256 in 2023, 294 in 2024, 163 in 2025, 240 in 2026.

How many Deep learning · optimization papers are at NeurIPS 2026?

NeurIPS 2026 has 103 Deep learning · optimization papers, versus 62 the year before.

How many Deep learning · optimization papers are at ICLR 2026?

ICLR 2026 has 44 Deep learning · optimization papers, versus 51 the year before.

How many Deep learning · optimization papers are at ICML 2026?

ICML 2026 has 86 Deep learning · optimization papers, versus 44 the year before.

How many Deep learning · optimization papers are at CVPR 2026?

CVPR 2026 has 7 Deep learning · optimization papers, versus 6 the year before.

Which conference publishes the most Deep learning · optimization papers?

NeurIPS, with 500 papers from 2023 to 2026.