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Team streamlines neural networks to be more adept at computing on encrypted data
Researchers at the NYU Center for Cyber Security at the NYU Tandon School of Engineering are rethinking basic functions that drive the ability of neural networks to make inferences on encrypted data. Their focus is on linear and non-linear operators, key features of neural network frameworks that, depending on the operation, introduce a heavy toll in time and computational resources.