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

51 papers, page 1 of 2

1. ICLR 2025A Coefficient Makes SVRG Effective
2. ICLR 2025A Stochastic Approach to the Subset Selection Problem via Mirror Descent
3. ICLR 2025A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
4. ICLR 2025A Truncated Newton Method for Optimal Transport
5. ICLR 2025Adaptive Gradient Clipping for Robust Federated Learning
6. ICLR 2025ADMM for Nonconvex Optimization under Minimal Continuity Assumption
7. ICLR 2025Aioli: A Unified Optimization Framework for Language Model Data Mixing
8. ICLR 2025An Effective Manifold-based Optimization Method for Distributionally Robust Classification
9. ICLR 2025Approximation algorithms for combinatorial optimization with predictions
10. ICLR 2025Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
11. ICLR 2025Bootstrapping Language Models with DPO Implicit Rewards
12. ICLR 2025Cauchy-Schwarz Regularizers
13. ICLR 2025Convex Formulations for Training Two-Layer ReLU Neural Networks
14. ICLR 2025Decentralized Optimization with Coupled Constraints
15. ICLR 2025Edge-aware Image Smoothing with Relative Wavelet Domain Representation
16. ICLR 2025Entropy-based Activation Function Optimization: A Method on Searching Better Activation Functions
17. ICLR 2025FlashRNN: I/O-Aware Optimization of Traditional RNNs on modern hardware
18. ICLR 2025Gradient correlation is a key ingredient to accelerate SGD with momentum
19. ICLR 2025Gradient descent with generalized Newton’s method
20. ICLR 2025How Does Critical Batch Size Scale in Pre-training?
21. ICLR 2025Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
22. ICLR 2025LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
23. ICLR 2025Latent Bayesian Optimization via Autoregressive Normalizing Flows
24. ICLR 2025Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
25. ICLR 2025Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization
26. ICLR 2025Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
27. ICLR 2025Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
28. ICLR 2025On the Almost Sure Convergence of the Stochastic Three Points Algorithm
29. ICLR 2025OPTAMI: Global Superlinear Convergence of High-order Methods
30. ICLR 2025Optimizing importance weighting in the presence of sub-population shifts
31. ICLR 2025Optimizing Neural Network Representations of Boolean Networks
32. ICLR 2025Optimizing Posterior Samples for Bayesian Optimization via Rootfinding
33. ICLR 2025Overcoming Lower-Level Constraints in Bilevel Optimization: A Novel Approach with Regularized Gap Functions
34. ICLR 2025Pareto Prompt Optimization
35. ICLR 2025ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization
36. ICLR 2025qNBO: quasi-Newton Meets Bilevel Optimization
37. ICLR 2025Revisiting Large-Scale Non-convex Distributionally Robust Optimization
38. ICLR 2025Second-Order Min-Max Optimization with Lazy Hessians
39. ICLR 2025Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
40. ICLR 2025The AdEMAMix Optimizer: Better, Faster, Older
41. ICLR 2025The Complexity of Two-Team Polymatrix Games with Independent Adversaries
42. ICLR 2025The Crucial Role of Samplers in Online Direct Preference Optimization
43. ICLR 2025The Directionality of Optimization Trajectories in Neural Networks
44. ICLR 2025To Clip or not to Clip: the Dynamics of SGD with Gradient Clipping in High-Dimensions
45. ICLR 2025Towards Faster Decentralized Stochastic Optimization with Communication Compression
46. ICLR 2025Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
47. ICLR 2025Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization
48. ICLR 2025Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
49. ICLR 2025Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model
50. ICLR 2025Weighted-Reward Preference Optimization for Implicit Model Fusion

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.