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Intellectual Property Protection for Distributed Neural Networks - Towards Confidentiality of Data, Model, and Inference
2018
Proceedings of the 15th International Joint Conference on e-Business and Telecommunications
Capitalizing on recent advances on HPC, GPUs, GPGPUs along with the rising amounts of publicly available labeled data; (Deep) Neural Networks (NN) have and will revolutionize virtually every current application domain as well as enable novel ones such as those on recognition, autonomous, predictive, resilient, selfmanaged, adaptive, and evolving applications. Nevertheless, it is to point out that NN training is rather resource intensive in data, time and energy; turning the resulting trained
doi:10.5220/0006854703130320
dblp:conf/icete/GomezIMD18
fatcat:nx27qgkhkfgg7lrm4ybxo65q2q