找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Privacy-Preserving Deep Learning; A Comprehensive Surv Kwangjo Kim,Harry Chandra Tanuwidjaja Book 2021 The Editor(s) (if applicable) and Th

[復(fù)制鏈接]
查看: 48818|回復(fù): 35
樓主
發(fā)表于 2025-3-21 17:35:29 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Privacy-Preserving Deep Learning
副標(biāo)題A Comprehensive Surv
編輯Kwangjo Kim,Harry Chandra Tanuwidjaja
視頻videohttp://file.papertrans.cn/757/756070/756070.mp4
概述Provides an overview of deep learning-based privacy-preserving.Discusses privacy issues in machine learning as a service.Addresses learning as one of the challenges in the context of privacy-preservin
叢書(shū)名稱(chēng)SpringerBriefs on Cyber Security Systems and Networks
圖書(shū)封面Titlebook: Privacy-Preserving Deep Learning; A Comprehensive Surv Kwangjo Kim,Harry Chandra Tanuwidjaja Book 2021 The Editor(s) (if applicable) and Th
描述This book discusses the state-of-the-art in privacy-preserving deep learning (PPDL), especially? as a tool for machine learning as a service (MLaaS), which serves as an enabling technology by combining classical privacy-preserving and cryptographic protocols with deep learning. Google and Microsoft announced a major investment in PPDL in early 2019. This was followed by Google’s infamous announcement of “Private Join and Compute,” an open source PPDL tools based on secure multi-party computation (secure MPC) and homomorphic encryption (HE) in June of that year. One of the challenging issues concerning PPDL is selecting its practical applicability despite the gap between the theory and practice. In order to solve this problem, it has recently been proposed that in addition to classical privacy-preserving methods (HE, secure MPC, differential privacy, secure enclaves), new federated or split learning for PPDL should also be applied. This concept involves building a cloud framework that enables collaborative learning while keeping training data on client devices. This successfully preserves privacy and while allowing the framework to be implemented in the real world.?.?.This book prov
出版日期Book 2021
關(guān)鍵詞Privacy-Preserving; Deep Learning; Machine Learning as a Service; Data Privacy; Privacy Issue on Deep Le
版次1
doihttps://doi.org/10.1007/978-981-16-3764-3
isbn_softcover978-981-16-3763-6
isbn_ebook978-981-16-3764-3Series ISSN 2522-5561 Series E-ISSN 2522-557X
issn_series 2522-5561
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書(shū)目名稱(chēng)Privacy-Preserving Deep Learning影響因子(影響力)




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning被引頻次




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning被引頻次學(xué)科排名




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning年度引用




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning年度引用學(xué)科排名




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning讀者反饋




書(shū)目名稱(chēng)Privacy-Preserving Deep Learning讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶(hù)組沒(méi)有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 22:02:27 | 只看該作者
第156070主題貼--第2樓 (沙發(fā))
板凳
發(fā)表于 2025-3-22 03:41:59 | 只看該作者
板凳
地板
發(fā)表于 2025-3-22 08:10:30 | 只看該作者
第4樓
5#
發(fā)表于 2025-3-22 11:35:29 | 只看該作者
5樓
6#
發(fā)表于 2025-3-22 13:24:04 | 只看該作者
6樓
7#
發(fā)表于 2025-3-22 18:44:32 | 只看該作者
7樓
8#
發(fā)表于 2025-3-22 22:06:03 | 只看該作者
8樓
9#
發(fā)表于 2025-3-23 05:25:56 | 只看該作者
9樓
10#
發(fā)表于 2025-3-23 08:29:47 | 只看該作者
10樓
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-14 19:35
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
甘泉县| 波密县| 土默特左旗| 蚌埠市| 交城县| 马关县| 汕头市| 吴旗县| 新绛县| 罗江县| 遂昌县| 涟源市| 赣榆县| 玛曲县| 丹寨县| 拜泉县| 马关县| 玛沁县| 巴彦淖尔市| 张家港市| 博乐市| 凤台县| 原阳县| 桦川县| 上高县| 湛江市| 山阳县| 株洲市| 大方县| 象山县| 道孚县| 武威市| 措美县| 贵德县| 西贡区| 于田县| 花莲市| 富源县| 吉木乃县| 永济市| 威信县|