Glutinous
发表于 2025-3-25 04:41:22
http://reply.papertrans.cn/47/4667/466661/466661_21.png
投票
发表于 2025-3-25 07:37:51
Manuel Mazzara,Giancarlo Succi,Alexander Tormasovcision tree model and a client interested in classifying its private attribute vector using the server’s private model. The goal of the computation is to obtain the classification while preserving the privacy of both—the decision tree and the client input. After the computation, the client learns th
咆哮
发表于 2025-3-25 12:12:23
Manuel Mazzara,Giancarlo Succi,Alexander Tormasovcision tree model and a client interested in classifying its private attribute vector using the server’s private model. The goal of the computation is to obtain the classification while preserving the privacy of both—the decision tree and the client input. After the computation, the client learns th
Gum-Disease
发表于 2025-3-25 16:41:56
Manuel Mazzara,Giancarlo Succi,Alexander Tormasovcision tree model and a client interested in classifying its private attribute vector using the server’s private model. The goal of the computation is to obtain the classification while preserving the privacy of both—the decision tree and the client input. After the computation, the client learns th
钝剑
发表于 2025-3-25 20:35:31
http://reply.papertrans.cn/47/4667/466661/466661_25.png
RODE
发表于 2025-3-26 03:21:57
a analysis methods. While there have been impressive advances in machine learning and similar domains in recent years, this also gives rise to concerns regarding the protection of personal and otherwise sensitive data, especially if it is to be analysed by third parties, e.g. in collaborative settin
是剥皮
发表于 2025-3-26 05:10:22
Manuel Mazzara,Giancarlo Succi,Alexander Tormasovcision tree model and a client interested in classifying its private attribute vector using the server’s private model. The goal of the computation is to obtain the classification while preserving the privacy of both—the decision tree and the client input. After the computation, the client learns th
容易懂得
发表于 2025-3-26 10:45:06
http://reply.papertrans.cn/47/4667/466661/466661_28.png
ALERT
发表于 2025-3-26 14:56:35
ossible protection is offered by anonymization of the training data or training function with differential privacy. However, data scientists can choose between local and central differential privacy, and need to select meaningful privacy parameters .. A comparison of local and central differential p
恸哭
发表于 2025-3-26 17:08:07
Manuel Mazzara,Giancarlo Succi,Alexander Tormasovlopers use user stories to write code, these user stories are better representations of the actual code than that of the high-level product documentation. In this paper, we develop an automated approach using machine learning to generate access control information from a set of user stories that des