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

272 papers, page 1 of 6

1. ICML 2026A Constrained Optimization Perspective of Unrolled Transformers
2. ICML 2026A Fully First-Order Layer for Differentiable Optimization
3. ICML 2026A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
4. ICML 2026A Linearly Convergent Proximal Subgradient Algorithm for Sparse Portfolio Optimization with Transaction Cost
5. ICML 2026A Risk Decomposition Framework for Pre-hoc Fine-tuning Prediction
6. ICML 2026Accelerated Dual Method for Distributed Optimization: An Inexact-Gradient View of Local Updates
7. ICML 2026An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale
8. ICML 2026ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization
9. ICML 2026Asymmetric Perturbation in Solving Bilinear Saddle-Point Optimization
10. ICML 2026Black-Box Combinatorial Optimization with Order-Invariant Reinforcement Learning
11. ICML 2026Bottleneck Communication Delay Minimization for Communication-Efficient Decentralized Learning
12. ICML 2026Certificate-Guided Pruning for Stochastic Lipschitz Optimization
13. ICML 2026Complexity of Decentralized Optimization with Mixed Affine Constraints
14. ICML 2026Conformal Prediction for Early Stopping in Mixed Integer Optimization
15. ICML 2026Context Tuning for In-Context Optimization
16. ICML 2026Convergence Analysis of Decentralized Hessian-/Jacobian-Free Algorithm for Nonconvex Stochastic Bilevel Optimization
17. ICML 2026Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
18. ICML 2026CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning
19. ICML 2026DDSVM: A Differentiable Framework for Deep Support Vector Machines with Iterative Geometry-Aware Optimization
20. ICML 2026Decision-focused Sparse Tangent Portfolio Optimization
21. ICML 2026Depth over Fidelity in Fixed-Budget Noisy Evolution Strategies
22. ICML 2026Diffusion-based learning framework for Constrained Nonconvex Optimization with Weighted Bootstrapped Refinement
23. ICML 2026DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers
24. ICML 2026DREAM: Dual-Standard Semantic Homogeneity with Dynamic Optimization for Graph Learning with Label Noise
25. ICML 2026Dual Quaternion SE(3) Synchronization with Recovery Guarantees
26. ICML 2026Fast Spectrally Sparse Signal Reconstruction via Jacobi-Preconditioned Gradient Descent
27. ICML 2026Finding Stationary Points by Comparisons
28. ICML 2026Flatland: The Adventures of Gradient Descent with Large Step Sizes
29. ICML 2026From Optimization to Generalization under Heavy-Tailed Data: The Role of Gradient Clipping
30. ICML 2026Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
31. ICML 2026Gradient Flow Sampler-based Distributionally Robust Optimization
32. ICML 2026Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization
33. ICML 2026GradPower: Powering Gradients for Faster Language Model Pre-Training
34. ICML 2026GXPO: Group Cross-Lingual Relative Policy Optimization for Code Generation
35. ICML 2026HeraSys: Collaborative Serving of Multiple LLM Workflows via Fine-Grained End-to-End Optimization
36. ICML 2026Hom-PGD$^+$: Fast Reparameterized Optimization over Non-convex Ball-Homeomorphic Set
37. ICML 2026Improved Convergence Analysis of Topology Dependence in Decentralized SGD
38. ICML 2026Improved Stochastic Optimization of LogSumExp
39. ICML 2026In-Context Learning as Rate–Distortion Optimization
40. ICML 2026Incremental Learning of Sparse Attention Patterns in Transformers
41. ICML 2026Iterative Robust Satisficing: Minimizing Performance Degradation Under Distribution Shift
42. ICML 2026Learning Credal Ensembles via Distributionally Robust Optimization
43. ICML 2026LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding
44. ICML 2026Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
45. ICML 2026Local-Minima-Preserving Polynomial Relaxation of Ising Problems
46. ICML 2026Loss-Aware Distributionally Robust Optimization via Trainable Optimal Transport Ambiguity Sets
47. ICML 2026Lower Complexity Bounds for Nonconvex-Strongly-Convex Bilevel Optimization with First-Order Oracles
48. ICML 2026LS$^{2}$MC-GDA: A Smoothed Algorithm for Federated Stochastic Multi-Level Compositional Minimax Optimization
49. ICML 2026MoCL: Metabolic Optimization for Curvature-Aware Continual Learning
50. ICML 2026NEMO: Execution-Aware Optimization Modeling via Autonomous Coding Agents

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.