Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Massih-Reza Amini,Stéphane Canu,Grigorios Tsoumaka Conference p

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Deep Learning Based Urban Anomaly Prediction from Spatiotemporal Datas of interest (POI), roads, calendar, and weather that were collected via smart devices in the city. The extensive experiments show that our proposed framework outperforms baseline and state-of-the-art models.

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Detecting Anomalies with Autoencoders on Data Streamspting to anomalies and thereby reducing their sensitivity to such data by introducing a simple modification to the models’ training approach. Our experimental results indicate that our solution achieves a larger gap between the losses on anomalous and normal instances than a conventional training pr

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Juncheng Liu,Yiwei Wang,Bryan Hooi,Renchi Yang,Xiaokui Xiaotzung des Autorenteams: zwei Promotions-Studenten und ein Professor. In die Darstellung der einzelnen Themen wie Folgen, unendliche Reihen, Stetigkeit, Differential- und Integralrechnung, fließen so einerseits die Erfahrungen eines Hochschullehrers – der die Vorlesung mehrmals gehalten hat – und and

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Structured Nonlinear Discriminant Analysis (PCA)—optimize data representation with respect to an information theoretic criterion. For time series analysis these traditional techniques are typically insufficient. In this work we propose an extension to linear discriminant analysis that allows to learn a data representation based on an algebr

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