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Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks.

, , , , и . EMBC, стр. 2486-2491. IEEE, (2019)

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Arno Knobbe

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Preference rules for label ranking: Mining patterns in multi-target relations., , , , и . CoRR, (2019)Distance-Based Decision Tree Algorithms for Label Ranking., , , и . EPIA, том 9273 из Lecture Notes in Computer Science, стр. 525-534. Springer, (2015)Biclustering Multivariate Time Series., , и . IDA, том 10584 из Lecture Notes in Computer Science, стр. 27-39. Springer, (2017)Efficient Algorithms for Finding Richer Subgroup Descriptions in Numeric and Nominal Data., , , и . ICDM, стр. 499-508. IEEE Computer Society, (2012)Discovering Local Subgroups, with an Application to Fraud Detection., , , и . PAKDD (1), том 7818 из Lecture Notes in Computer Science, стр. 1-12. Springer, (2013)Analysing Binary Associations., и . KDD, стр. 311-314. AAAI Press, (1996)Propositionalisation and Aggregates., , и . PKDD, том 2168 из Lecture Notes in Computer Science, стр. 277-288. Springer, (2001)Multilayer Perceptron for Label Ranking., , , и . ICANN (2), том 7553 из Lecture Notes in Computer Science, стр. 25-32. Springer, (2012)Bipeline: A Web-Based Visualization Tool for Biclustering of Multivariate Time Series., , , и . ECML/PKDD (3), том 9853 из Lecture Notes in Computer Science, стр. 12-16. Springer, (2016)Exceptional Model Mining - Supervised descriptive local pattern mining with complex target concepts., , и . Data Min. Knowl. Discov., 30 (1): 47-98 (2016)