Copying Machine Learning Classifiers

Copying Machine Learning Classifiers

We study copying of machine learning classifiers, an agnostic technique to replicate the decision behavior of any classifier. We develop the theory behind the problem of copying, highlighting its properties, and propose a framework to copy the decision behavior of any classifier using no prior knowl...

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Bibliographic Details
Main Authors: Irene Unceta, Jordi Nin, Oriol Pujol
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Applied machine learning
classification
copying
differential replication
fidelity
Online Access:https://ieeexplore.ieee.org/document/9181566/

Internet

https://ieeexplore.ieee.org/document/9181566/

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