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Learning and Evaluation in Presence of Non-i.i.d. Label Noise., , , , , , and . AISTATS, volume 33 of JMLR Workshop and Conference Proceedings, page 293-302. JMLR.org, (2014)Scalable Generalized Dynamic Topic Models., , , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1427-1435. PMLR, (2018)Online Anomaly Detection under Adversarial Impact., and . AISTATS, volume 9 of JMLR Proceedings, page 405-412. JMLR.org, (2010)Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text., , , , and . ACL (1), page 4061-4071. Association for Computational Linguistics, (2019)The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning., and . NIPS, page 2438-2446. (2011)Data-Dependent Generalization Bounds for Multi-Class Classification., , , and . IEEE Trans. Information Theory, 65 (5): 2995-3021 (2019)Decoding Brain States during Auditory Perception by Supervising Unsupervised Learning., , , and . JCSE, 7 (2): 112-121 (2013)Bayesian Nonlinear Support Vector Machines for Big Data., , , and . ECML/PKDD (1), volume 10534 of Lecture Notes in Computer Science, page 307-322. Springer, (2017)Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms., , , , and . ECML/PKDD (2), volume 9285 of Lecture Notes in Computer Science, page 137-153. Springer, (2015)Multi-task Learning for Computational Biology: Overview and Outlook., , and . Empirical Inference, page 117-127. Springer, (2013)