发布求助
文献互助 智能选刊 最新文献

Frontiers of Data-Intensive Compute Algorithms: Sustainable MLOps and Beyond

2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2020-09-01 DOI:10.1109/synasc51798.2020.00010
{"title":"Frontiers of Data-Intensive Compute Algorithms: Sustainable MLOps and Beyond","authors":"","doi":"10.1109/synasc51798.2020.00010","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":278104,"journal":{"name":"2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/synasc51798.2020.00010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
分享
查看原文 本刊更多论文
数据密集型计算算法的前沿:可持续的MLOps及以后
本文章由计算机程序翻译，如有差异，请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信