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Deep Models Under the GAN
Briland Hitaj, Giuseppe Ateniese, Fernando Pérez‐Cruz
Stevens Institute of Technology
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摘要与影响
摘要 · 完整
Deep Learning has recently become hugely popular in machine learning for its ability to solve end-to-end learning systems, in which the features and the classifiers are learned simultaneously, providing significant improvements in classification accuracy in the presence of highly-structured and large databases.
逐年被引趋势
2121060
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关键指标
1,312
被引次数 · OpenAlex
41.47
领域内被引倍数
同类平均 = 1
同类平均 = 1
前 0.2%
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17
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学术脉络
学科主题
计算机 / AIPrivacy-Preserving Technologies in Data
Adversarial Robustness in Machine Learning · Advanced Neural Network Applications
参考文献 17
Text Understanding from Scratch
被引 421Xiang Zhang, Yann LeCun · arXiv (Cornell University) · 2015
Learning Deep Architectures for AI
被引 5,076Yoshua Bengio · now publishers, Inc. eBooks · 2009
Solving large scale linear prediction problems using stochastic gradient descent algorithms
被引 1,149Tong Zhang · 2004
此处列出前 3 条
引用本文 1,312
Federated Machine Learning
被引 6,120Qiang Yang, Yang Liu, Tianjian Chen · ACM Transactions on Intelligent Systems and Technology · 2019
The future of digital health with federated learning
被引 2,799Nicola Rieke, Jonny Hancox, Wenqi Li · npj Digital Medicine · 2020
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
被引 2,512Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang · IEEE Communications Surveys & Tutorials · 2020
按被引量排序,此处列出前 3 条