Amazon Technologies, Inc.

Hao Zhou

Stefano Soatto

Wei Xia

Joseph Patrick Tighe

Jonathan Wu

Yuanjun Xiong

Shuo Yang

Xiang Xu

Machine learning models may be generated that are compatible with another machine learning model and satisfy a resource constraint. Techniques that ensure weight compatibility and architectural compatibility between a machine learning model being created to be compatible with another machine learning model are applied. The resource constraint is enforced so that the generated machine learning model also fits within the resource constraint.

Compatible machine learning model generation within resource constraints

A system for evaluating a biometric authorization system is described. The biometric authorization system is configured to apply a facial recognition model to image data to make an authorization determination based on detection of synthesized image data and based on matching a reference image to the image data. The system is also configured to execute one or more synthetic image data attack protocols to evaluate the biometric authorization system. The system also generates, according to one or more synthetic image data generation techniques, an evaluation set of image data comprising synthesized representations of a target and sends one or more authorization requests using the evaluation set of image data to the biometric authorization system. The system generates an evaluation of the biometric authorization system for synthetic image data attack analysis based on respective responses to the one or more authorization requests received from the biometric authorization system.

Evaluating biometric authorization systems with synthesized images

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Seattle, WA, United States of America

Hao Zhou