66 citations · 109 across the 12 of their papers we have counts for
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cs.LG2020
Data Poisoning Attacks on Regression Learning and Corresponding Defenses
Nicolas Michael Müller, Daniel Kowatsch, Konstantin Böttinger
Adversarial data poisoning is an effective attack against machine learning and threatens model integrity by introducing poisoned data into the training dataset. So far, it has been…
cs.LG2019★ 28 cited
Identifying Mislabeled Instances in Classification Datasets
Nicolas Michael Müller, Karla Markert
A key requirement for supervised machine learning is labeled training data, which is created by annotating unlabeled data with the appropriate class. Because this process can in ma…