Privacy Preserving Back Propagation Algorithm - Sayyad, Suhel;Kulkarni, Prakash
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The learning problems have to be concerned about distributed input data, because of gradual expansion of distributed computing environment. It is important to address the privacy concern of each data holder by extending the privacy preservation concept to original learning algorithms, to enhance co-operations in learning. In this work, focus is on protecting the privacy in a significant learning model, multilayer neural networks.

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Produktbeschreibung
The learning problems have to be concerned about distributed input data, because of gradual expansion of distributed computing environment. It is important to address the privacy concern of each data holder by extending the privacy preservation concept to original learning algorithms, to enhance co-operations in learning. In this work, focus is on protecting the privacy in a significant learning model, multilayer neural networks.
Autorenporträt
Mr. Suhel S Sayyad has completed his M.Tech in Computer Science and Engineering from Walchand College of Engineering Sangli. He has received silver medal for his UG and PG degree. Currently, he is working as Assistant Professor at Annasaheb Dange College of Engineering and Technology Ashta. His research interest are Neural Networks, Databases.