Chrome Extension
WeChat Mini Program
Use on ChatGLM

Maxima of the Aα-Index of Graphs with Given Size and Domination Number

Discrete Applied Mathematics(2024)CCF CSCI 3区

Yancheng Teachers Univ

Cited 0|Views2
Abstract
The Aα-matrix of a graph G was defined by Nikiforov in 2017 as Aα(G)=αD(G)+(1−α)A(G), where α∈[0,1], D(G) and A(G) are the diagonal matrix of degrees and the adjacency matrix respectively. The largest eigenvalue of Aα(G) is called Aα-index of G. In this paper, we completely determine the extremal graphs with maximal Aα-index among all graphs with size m , domination number γ and no isolated vertices for α∈[12,1).
More
Translated text
Key words
Domination number,Size,Extremal graph
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper

要点】:本文确定了在给定图的大小、控制数以及无孤立顶点的条件下,α指数最大化的极值图,创新点在于对α指数的极值图进行了完整分类。

方法】:通过研究图G的Aα矩阵,即Aα(G)=αD(G)+(1−α)A(G),其中D(G)为度对角矩阵,A(G)为邻接矩阵,并利用α指数(Aα矩阵的最大特征值)来寻找极值图。

实验】:文中未具体描述实验过程,但给出了在α∈[1/2,1)范围内,所有大小为m,控制数为γ,且无孤立顶点的图中,Aα指数最大的图的分类结果,未提及具体数据集名称。