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中国科学院计算技术研究所机构知识库
Institute of Computing Technology, Chinese Academy IR
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浏览/检索结果:
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Personalized Federated Learning With Adaptive Batchnorm for Healthcare
期刊论文
IEEE TRANSACTIONS ON BIG DATA, 2024, 卷号: 10, 期号: 6, 页码: 915-925
作者:
Lu, Wang
;
Wang, Jindong
;
Chen, Yiqiang
;
Qin, Xin
;
Xu, Renjun
;
Dimitriadis, Dimitrios
;
Qin, Tao
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/12/06
Medical services
Collaborative work
Data models
Adaptation models
Computational modeling
Machine learning
Data privacy
Distributed computing
federated learning
personalization
batch normalization
healthcare
DiSAuth: A DNS-based secure authorization framework for protecting data decoupled from applications
期刊论文
COMPUTER NETWORKS, 2024, 卷号: 254, 页码: 18
作者:
Li, Ying
;
Wei, Jiuqi
;
Fei, Ziyu
;
Fu, Yufan
;
Lee, Xiaodong
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2024/12/06
Authorization
Data security and privacy
DNS
Blockchain
Streaming Data Collection With a Private Sketch-Based Protocol
期刊论文
IEEE INTERNET OF THINGS JOURNAL, 2024, 卷号: 11, 期号: 15, 页码: 25950-25967
作者:
Li, Ying
;
Lee, Xiaodong
;
Peng, Botao
;
Palpanas, Themis
;
Xue, Jingan
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2024/12/06
Privacy
Estimation
Data collection
Frequency estimation
Protocols
Protection
Internet
local differential privacy (LDP)
mean estimation
sketch
Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System
期刊论文
SYMMETRY-BASEL, 2024, 卷号: 16, 期号: 1, 页码: 29
作者:
Yao, Zhengyi
;
Tan, Liang
;
Yi, Junhao
;
Fu, Luxia
;
Zhang, Zhuang
;
Tan, Xinghong
;
Xie, Jingxue
;
She, Kun
;
Yang, Peng
;
Wu, Wanjing
;
Ye, Danlian
;
Yu, Ziyuan
收藏
  |  
浏览/下载:10/0
  |  
提交时间:2024/05/20
data privacy
location privacy
smart logistics platform
privacy protection
Poseidon-NDP: Practical Fully Homomorphic Encryption Accelerator Based on Near Data Processing Architecture
期刊论文
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS, 2023, 卷号: 42, 期号: 12, 页码: 4749-4762
作者:
Yang, Yinghao
;
Lu, Hang
;
Li, Xiaowei
收藏
  |  
浏览/下载:37/0
  |  
提交时间:2024/05/20
FPGA accelerator
fully homomorphic encryption (FHE)
near data processing (NDP)
privacy computing
Data Security and Privacy Challenges of Computing Offloading in FINs
期刊论文
IEEE NETWORK, 2020, 卷号: 34, 期号: 2, 页码: 14-20
作者:
Wang, Fei
;
Diao, Boyu
;
Sun, Tao
;
Xu, Yongjun
收藏
  |  
浏览/下载:93/0
  |  
提交时间:2020/12/10
Task analysis
Cloud computing
Data privacy
Edge computing
Smart homes
Data security
Supervised Collaborative Filtering Based on Ridge Alternating Least Squares and Iterative Projection Pursuit
期刊论文
IEEE ACCESS, 2017, 卷号: 5, 页码: 6600-6607
作者:
Chen, Bo-Wei
;
Ji, Wen
;
Rho, Seungmin
;
Gu, Yu
收藏
  |  
浏览/下载:46/0
  |  
提交时间:2019/12/12
Incomplete data analysis
privacy preservation
supervised collaborative filtering
collaborative filtering (CF)
alternating least squares (ALS)
supervised data imputation
data imputation
singular value decomposition (SVD)
supervised nonnegative matrix factorization (NMF)
recommendation system
low-rank matrix approximation
matrix completion
matrix factorization
iterative projection pursuit
A semi-supervised privacy-preserving clustering algorithm for healthcare
期刊论文
PEER-TO-PEER NETWORKING AND APPLICATIONS, 2016, 卷号: 9, 期号: 5, 页码: 864-875
作者:
Huang, Meiyu
;
Chen, Yiqiang
;
Chen, Bo-Wei
;
Liu, Junfa
;
Rho, Seungmin
;
Ji, Wen
收藏
  |  
浏览/下载:45/0
  |  
提交时间:2019/12/13
Privacy-preserving cloud clustering
Data perturbation
Semi-supervised
Large margin nearest cluster metric
Brain fiber
Predicting the attributes of social network users using a graph-based machine learning method
期刊论文
COMPUTER COMMUNICATIONS, 2016, 卷号: 73, 页码: 3-11
作者:
Ding, Yuxin
;
Yan, Shengli
;
Zhang, YiBin
;
Dai, Wei
;
Dong, Li
收藏
  |  
浏览/下载:44/0
  |  
提交时间:2019/12/13
Social network analysis
Data mining
Social network privacy
Semi-supervised learning
Information inference
Self-destructing Instant Messages by Employing KAD DHT Network
期刊论文
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2015, 卷号: 31, 期号: 4, 页码: 1169-1184
作者:
Deng, Yuhui
;
Zhang, Zhen
;
Chen, Zhike
;
Lu, Lijuan
收藏
  |  
浏览/下载:45/0
  |  
提交时间:2019/12/13
self-destructing
data privacy
instant messages
DHT
P2P