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Found 2 papers, 1 papers with code
RAILS: A Robust Adversarial Immune-inspired Learning System
Initializing a population of exemplars that is balanced across classes, RAILS starts from a uniform label distribution that encourages diversity and uses an evolutionary optimization process to adaptively adjust the predictive label distribution in a manner that emulates the way the natural immune system recognizes novel pathogens.
RAILS: A Robust Adversarial Immune-inspired Learning System
RAILS incorporates an Adaptive Immune System Emulation (AISE), which emulates in silico the biological mechanisms that are used to defend the host against attacks by pathogens.
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