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pro vyhledávání: '"Krčo, Nataša"'
Membership Inference Attacks (MIAs) are widely used to evaluate the propensity of a machine learning (ML) model to memorize an individual record and the privacy risk releasing the model poses. MIAs are commonly evaluated similarly to ML models: the M
Externí odkaz:
http://arxiv.org/abs/2405.15423
Most research on fair machine learning has prioritized optimizing criteria such as Demographic Parity and Equalized Odds. Despite these efforts, there remains a limited understanding of how different bias mitigation strategies affect individual predi
Externí odkaz:
http://arxiv.org/abs/2302.07185
Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields.
Externí odkaz:
http://arxiv.org/abs/2207.00551