Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.24552 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918491700854784 |
|---|---|
| author | Zhong, Jindi Yin, Congyaohui Zhang, Zhaorong Zhang, Huanshui |
| author_facet | Zhong, Jindi Yin, Congyaohui Zhang, Zhaorong Zhang, Huanshui |
| contents | This paper proposes a novel second-order optimization algorithm based on the Optimal Control Principle (OCP), applicable to large-scale optimization problems in neural network training. The algorithm has a computational complexity of O(d) and strong robustness. Extensive experiments on multiple benchmarks demonstrate the significant superiority of the proposed method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_24552 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OCP-GN: A Scalable Second-order Optimizer for Stochastic Optimization Zhong, Jindi Yin, Congyaohui Zhang, Zhaorong Zhang, Huanshui Computer Vision and Pattern Recognition Optimization and Control This paper proposes a novel second-order optimization algorithm based on the Optimal Control Principle (OCP), applicable to large-scale optimization problems in neural network training. The algorithm has a computational complexity of O(d) and strong robustness. Extensive experiments on multiple benchmarks demonstrate the significant superiority of the proposed method. |
| title | OCP-GN: A Scalable Second-order Optimizer for Stochastic Optimization |
| topic | Computer Vision and Pattern Recognition Optimization and Control |
| url | https://arxiv.org/abs/2512.24552 |