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Interpretation of linear classifiers by means of feature relevance bounds., , , and . Neurocomputing, (2018)Local Reject Option for Deterministic Multi-class SVM., , , , and . ICANN (2), volume 9887 of Lecture Notes in Computer Science, page 251-258. Springer, (2016)Faster Confidence Intervals for Item Response Theory via an Approximate Likelihood Profile., , and . EDM, International Educational Data Mining Society, (2022)Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning., , and . ICANN (1), volume 9886 of Lecture Notes in Computer Science, page 510-517. Springer, (2016)Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors., , , , , , , , , and . Trans. Recomm. Syst., 2 (4): 30:1-30:37 (December 2024)When can unlabeled data improve the learning rate?, , , , , and . COLT, volume 99 of Proceedings of Machine Learning Research, page 1500-1518. PMLR, (2019)Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors., , , , , , and . WWW, page 2411-2421. ACM, (2022)FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration., , , , and . CoRR, (2019)How to Compare Adversarial Robustness of Classifiers from a Global Perspective., , and . ICANN (1), volume 12891 of Lecture Notes in Computer Science, page 29-41. Springer, (2021)Guiding Information: Supervised Models and their Relationship with Data.. Bielefeld University, Germany, (2023)