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pro vyhledávání: '"Roschmann, Simon"'
For real-world applications of machine learning (ML), it is essential that models make predictions based on well-generalizing features rather than spurious correlations in the data. The identification of such spurious correlations, also known as shor
Externí odkaz:
http://arxiv.org/abs/2302.04246
Data poisoning is one of the most relevant security threats against machine learning and data-driven technologies. Since many applications rely on untrusted training data, an attacker can easily craft malicious samples and inject them into the traini
Externí odkaz:
http://arxiv.org/abs/2104.06744
Publikováno v:
Proceedings of the 2020 Workshop on DYnamic and Novel Advances in Machine Learning and Intelligent Cyber Security.
Data poisoning is one of the most relevant security threats against machine learning and data-driven technologies. Since many applications rely on untrusted training data, an attacker can easily craft malicious samples and inject them into the traini
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ebe545bb9a51e273eb17fe35c64c2aa0
https://doi.org/10.1145/3477997.3478017
https://doi.org/10.1145/3477997.3478017
