半定优化的一种新的原对偶内点算法

2014 International Conference on Information Science & Applications (ICISA) Pub Date : 2014-05-06 DOI:10.1109/ICISA.2014.6847334

Yong-Hoon Lee, Jin-Hee Jin, G. Cho

{"title":"半定优化的一种新的原对偶内点算法","authors":"Yong-Hoon Lee, Jin-Hee Jin, G. Cho","doi":"10.1109/ICISA.2014.6847334","DOIUrl":null,"url":null,"abstract":"We propose a new primal-dual interior-point algorithm for semidefinite optimization(SDO) based on an eligible barrier function. New search directions and proximity measures are proposed based on the barrier function. We show that the algorithm has O(√n log(n/ε)) and O(√n(log n)log(n/ε)) complexity results for small- and large-update methods, respectively. These are the best known complexity results for such methods.","PeriodicalId":117185,"journal":{"name":"2014 International Conference on Information Science & Applications (ICISA)","volume":"241 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Primal-Dual Interior-Point Algorithm for Semidefinite Optimization\",\"authors\":\"Yong-Hoon Lee, Jin-Hee Jin, G. Cho\",\"doi\":\"10.1109/ICISA.2014.6847334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a new primal-dual interior-point algorithm for semidefinite optimization(SDO) based on an eligible barrier function. New search directions and proximity measures are proposed based on the barrier function. We show that the algorithm has O(√n log(n/ε)) and O(√n(log n)log(n/ε)) complexity results for small- and large-update methods, respectively. These are the best known complexity results for such methods.\",\"PeriodicalId\":117185,\"journal\":{\"name\":\"2014 International Conference on Information Science & Applications (ICISA)\",\"volume\":\"241 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Information Science & Applications (ICISA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISA.2014.6847334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Information Science & Applications (ICISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISA.2014.6847334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

提出了一种新的基于合适的障碍函数的半定优化(SDO)的原对偶内点算法。提出了基于障碍函数的新的搜索方向和接近度量。我们证明了该算法对于小更新和大更新方法分别具有O(√n log(n/ε))和O(√n(log n)log(n/ε))复杂度结果。这些是此类方法最著名的复杂性结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A New Primal-Dual Interior-Point Algorithm for Semidefinite Optimization

We propose a new primal-dual interior-point algorithm for semidefinite optimization(SDO) based on an eligible barrier function. New search directions and proximity measures are proposed based on the barrier function. We show that the algorithm has O(√n log(n/ε)) and O(√n(log n)log(n/ε)) complexity results for small- and large-update methods, respectively. These are the best known complexity results for such methods.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2014 International Conference on Information Science & Applications (ICISA)

自引率

0.00%

发文量