Special session: Towards an agile design methodology for efficient, reliable, and secure ML systems
The real-world use cases of Machine Learning (ML) have exploded over the past few years.
However, the current computing infrastructure is insufficient to support all real-world …
However, the current computing infrastructure is insufficient to support all real-world …
Adding adversarial robustness to trained machine learning models
One or more hardened machine learning models are secured against adversarial attacks by
adding adversarial protection to one or more previously trained machine learning models …
adding adversarial protection to one or more previously trained machine learning models …
Robustness Assurance Quotient: Demonstrating Context Matters for AI Performance and ML Security
S Lefcourt, N Gordon, H Wong… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
We present a novel approach to developing robust AI in light of context-varying situations.
This methodology harnesses a suite of indicators to establish a Robustness Assurance …
This methodology harnesses a suite of indicators to establish a Robustness Assurance …