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Sayin, Burcu (author), Yang, J. (author), Passerini, Andrea (author), Casati, Fabio (author)
In this paper, we argue that the way we have been training and evaluating ML models has largely forgotten the fact that they are applied in an organization or societal context as they provide value to people. We show that with this perspective we fundamentally change how we evaluate and select machine learning models.
conference paper 2023
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Yang, Shufan (author), Le Kernec, Julien (author), Romain, Olivier (author), Fioranelli, F. (author), Cadart, Pierre (author), Fix, Jeremy (author), Ren, Chengfang (author), Manfredi, Giovanni (author), Letertre, Thierry (author)
journal article 2023
document
Nadeem, A. (author), Verwer, S.E. (author), Yang, Shanchieh Jay (author)
The evolving nature of the tactics, techniques, and procedures used by cyber adversaries have made signature and template based methods of modeling adversary behavior almost infeasible. We are moving into an era of data-driven autonomous cyber defense agents that learn contextually meaningful adversary behaviors from observables. In this chapter...
book chapter 2023