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

953 papers, page 1 of 20

1. CVPR 2026Beyond Myopic Alignment Lookahead Optimization for Online Class-Incremental Learning
2. CVPR 2026Coverage Optimization for Camera View Selection
3. CVPR 2026Edges Compete for Trust Group Relative Edge Optimization for Building
4. CVPR 2026Its Never Too Late Noise Optimization for Collapse Recovery in
5. CVPR 2026Learnability-Driven Submodular Optimization for Active Roadside 3D Detection
6. CVPR 2026Pip-Stereo Progressive Iterations Pruner for Iterative Optimization based Stereo Matching
7. CVPR 2026TESO Online Tracking of Essential Matrix by Stochastic Optimization
8. ICLR 2026A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
9. ICLR 2026Beyond Short Steps in Frank-Wolfe Algorithms
10. ICLR 2026Cautious Weight Decay
11. ICLR 2026Clipped Gradient Methods for Nonsmooth Convex Optimization under Heavy-Tailed Noise: A Refined Analysis
12. ICLR 2026Combinatorial Bandit Bayesian Optimization for Tensor Outputs
13. ICLR 2026Communication-Efficient Decentralized Optimization via Double-Communication Symmetric ADMM
14. ICLR 2026Composite Optimization with Error Feedback: the Dual Averaging Approach
15. ICLR 2026Convergence of Muon with Newton-Schulz
16. ICLR 2026Deep FlexQP: Accelerated Nonlinear Programming via Deep Unfolding
17. ICLR 2026Discounted Online Convex Optimization: Uniform Regret Across a Continuous Interval
18. ICLR 2026DNT: a Deeply Normalized Transformer that can be trained by Momentum SGD
19. ICLR 2026Faster Gradient Methods for Highly-smooth Stochastic Bilevel Optimization
20. ICLR 2026FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
21. ICLR 2026From Sorting Algorithms to Scalable Kernels: Bayesian Optimization in High-Dimensional Permutation Spaces
22. ICLR 2026GoalRank: Group-Relative Optimization for a Large Ranking Model
23. ICLR 2026Gradient-Based Diversity Optimization with Differentiable Top-$k$ Objective
24. ICLR 2026Gradient-Normalized Smoothness for Optimization with Approximate Hessians
25. ICLR 2026Incorporating Expert Priors into Bayesian Optimization via Dynamic Mean Decay
26. ICLR 2026Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme
27. ICLR 2026LMask: Learn to Solve Constrained Routing Problems with Lazy Masking
28. ICLR 2026Local Entropy Search over Descent Sequences for Bayesian Optimization
29. ICLR 2026Machine Unlearning under Retain–Forget Entanglement
30. ICLR 2026MaskInversion: Localized Embeddings via Optimization of Explainability Maps
31. ICLR 2026Mitigating Mismatch within Reference-based Preference Optimization
32. ICLR 2026MuonBP: Faster Muon via Block-Periodic Orthogonalization
33. ICLR 2026On The Surprising Effectiveness of a Single Global Merging in Decentralized Learning
34. ICLR 2026Online Black-Box Prompt Optimization with Regret Guarantees under Noisy Feedback
35. ICLR 2026Pinet: Optimizing hard-constrained neural networks with orthogonal projection layers
36. ICLR 2026Reducing Contextual Stochastic Bilevel Optimization via Structured Function Approximation
37. ICLR 2026Robust Optimization for Mitigating Reward Hacking with Correlated Proxies
38. ICLR 2026Scalable Second-order Riemannian Optimization for $K$-means Clustering
39. ICLR 2026Single-Loop Byzantine-Resilient Federated Bilevel Optimization
40. ICLR 2026Soft Quality-Diversity Optimization
41. ICLR 2026Special Unitary Parameterized Estimators of Rotation
42. ICLR 2026SPRIG: Improving Large Language Model Performance by System Prompt Optimization
43. ICLR 2026Stop Guessing: Choosing the Optimization-Consistent Uncertainty Measurement for Evidential Deep Learning
44. ICLR 2026Strongly Convex Sets in Riemannian Manifolds
45. ICLR 2026Submodular Function Minimization with Dueling Oracle
46. ICLR 2026SVD Provably Denoises Nearest Neighbor Data
47. ICLR 2026Symmetry-Aware Bayesian Optimization via Max Kernels
48. ICLR 2026The Potential of Second-Order Optimization for LLMs: A Study with Full Gauss-Newton
49. ICLR 2026Thinking on the Fly: Test-Time Reasoning Enhancement via Latent Thought Policy Optimization
50. ICLR 2026Token-Importance Guided Direct Preference Optimization

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.