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Poster framing adversarial machine learning as mending the fence before the sheep are lost: designing new attack algorithms that reveal weak spots in tabular models before they fail in use. Summarises the seven imperceptibility properties for tabular data and the research gaps they expose.
If the poster does not render here, use Open PDF above.