4 citations · 9 across the 8 of their papers we have counts for
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cs.SD2022★ 2 cited
Concept-Based Techniques for "Musicologist-friendly" Explanations in a Deep Music Classifier
Francesco Foscarin, Katharina Hoedt, Verena Praher +2
Current approaches for explaining deep learning systems applied to musical data provide results in a low-level feature space, e.g., by highlighting potentially relevant time-freque…
eess.AS2022
Defending a Music Recommender Against Hubness-Based Adversarial Attacks
Katharina Hoedt, Arthur Flexer, Gerhard Widmer
Adversarial attacks can drastically degrade performance of recommenders and other machine learning systems, resulting in an increased demand for defence mechanisms. We present a ne…