论文标题
基于辫子的建筑搜索
Braid-based architecture search
论文作者
论文摘要
在本文中，我们提出了基于编织理论的神经网络结构优化的方法。本文描述了编织理论的基础知识，用于应用于神经网络的图形结构的描述。它显示了如何使用神经网络层之间的编织结构构建各种拓扑的网络。将基于辫子理论的神经网络的运行与均匀的深神经网络和与辫子排序相对应的层之间随机相交的网络进行了比较。获得的结果显示了基于辫子的网络比在分类问题中的可比较体系结构的优势。
In this article, we propose the approach to structural optimization of neural networks, based on the braid theory. The paper describes the basics of braid theory as applied to the description of graph structures of neural networks. It is shown how networks of various topologies can be built using braid structures between layers of neural networks. The operation of a neural network based on the braid theory is compared with a homogeneous deep neural network and a network with random intersections between layers that do not correspond to the ordering of the braids. Results are obtained showing the advantage of braid-based networks over comparable architectures in classification problems.
