首页> Frontiers in artificial intelligence> Lipschitz-based robustness estimation for hyperdimensional learning.

Lipschitz-based robustness estimation for hyperdimensional learning.

导出 LinkOut

翻译打印收藏纠错

第一作者： Calvin,Yeung

第一单位： Department of Computer Science, University of California, Irvine, Irvine, CA, United States.

作者： Calvin,Yeung ^[1] ; Hamza,Errahmouni Barkam ^[1] ; Zhuowen,Zou ^[1] ; Sanggeon,Yun ^[1] ; Nathaniel D,Bastian ^[2] ; Mohsen,Imani ^[1]

作者单位： Department of Computer Science, University of California, Irvine, Irvine, CA, United States. ^[1] Department of Electrical Engineering & Computer Science, United States Military Academy, West Point, NY, United States. ^[2]

关键词 adversarial attacks classification hyperdimensional computing robustness vector symbolic architectures

DOI 10.3389/frai.2025.1637105

PMID 41041082

发布时间 2025-10-05

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览0

Frontiers in artificial intelligence

2025年8卷

1637105页

相似文献

中文期刊
外文期刊
学位论文
会议论文

浏览0

点击下载本期目录封面

Frontiers in artificial intelligence

2025年8卷

1637105页

检索历史清除

Lipschitz-based robustness estimation for hyperdimensional learning.

Frontiers in artificial intelligence

相似文献

同项目论文

Frontiers in artificial intelligence

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

Lipschitz-based robustness estimation for hyperdimensional learning.

Frontiers in artificial intelligence

相似文献

同项目论文

Frontiers in artificial intelligence

相关期刊

检索历史清除