Pattern recognition and classification for multivariate time series S Spiegel, J Gaebler, A Lommatzsch, E De Luca, S Albayrak Proceedings of the fifth international workshop on knowledge discovery from …, 2011 | 97 | 2011 |
Link prediction on evolving data using tensor factorization S Spiegel, J Clausen, S Albayrak, J Kunegis New Frontiers in Applied Data Mining: PAKDD 2011 International Workshops …, 2012 | 87 | 2012 |
Hydra: a hybrid recommender system [cross-linked rating and content information] S Spiegel, J Kunegis, F Li Proceedings of the 1st ACM international workshop on Complex networks meet …, 2009 | 47 | 2009 |
Approximation of diagonal line based measures in recurrence quantification analysis D Schultz, S Spiegel, N Marwan, S Albayrak Physics Letters A 379 (14-15), 997-1011, 2015 | 37 | 2015 |
Cost-sensitive learning for predictive maintenance S Spiegel, F Mueller, D Weismann, J Bird arXiv preprint arXiv:1809.10979, 2018 | 29 | 2018 |
Fast time series classification under lucky time warping distance S Spiegel, BJ Jain, S Albayrak Proceedings of the 29th Annual ACM Symposium on Applied Computing, 71-78, 2014 | 24 | 2014 |
A recurrence plot-based distance measure S Spiegel, JB Jain, S Albayrak Translational Recurrences: From Mathematical Theory to Real-World …, 2014 | 24 | 2014 |
A hybrid approach to recommender systems based on matrix factorization S Spiegel Department for Agent Technologies and Telecommunications, Technical …, 2009 | 19 | 2009 |
Energy disaggregation meets heating control S Spiegel, S Albayrak Proceedings of the 29th Annual ACM Symposium on Applied Computing, 559-566, 2014 | 16 | 2014 |
Dimension Reduction in Dissimilarity Spaces for Time Series Classification B Jain, S Spiegel Advanced Analysis and Learning on Temporal Data (DOI: 10.1007/978-3-319 …, 2016 | 15 | 2016 |
Pattern recognition in multivariate time series: dissertation proposal S Spiegel, BJ Jain, EW De Luca, S Albayrak Proceedings of the 4th workshop on Workshop for Ph. D. students in …, 2011 | 15 | 2011 |
Approximate recurrence quantification analysis (aRQA) in code of best practice S Spiegel, D Schultz, N Marwan Recurrence Plots and Their Quantifications: Expanding Horizons: Proceedings …, 2016 | 14 | 2016 |
An order-invariant time series distance measure S Spiegel, S Albayrak KDIR. SciTePress Digital Library, 2012 | 14 | 2012 |
Time series classification using compressed recurrence plots T Michael, S Spiegel, S Albayrak Proceedings of ECML-PKDD, 2015 | 13 | 2015 |
Discovery of driving behavior patterns S Spiegel Smart Information Systems: Computational Intelligence for Real-Life …, 2015 | 13 | 2015 |
Transfer learning for time series classification in dissimilarity spaces S Spiegel Proceedings of AALTD 78, 2016 | 11 | 2016 |
MediaEval 2011 Affect Task: Violent Scene Detection combining audio and visual Features with SVM. E Acar, S Spiegel, S Albayrak, DAI Labor MediaEval, 2011 | 10 | 2011 |
Biomarker-based classification and localization of renal lesions using learned representations of histology—a machine learning approach to histopathology CAC Freyre, S Spiegel, C Gubser Keller, M Vandemeulebroecke, ... Toxicologic Pathology 49 (4), 798-814, 2021 | 9 | 2021 |
A Sliding Window Filter for Time Series Streams G Lesti, S Spiegel ECML PKDD 2017 - Workshop on IoT Large Scale Learning from Data Streams, 2017 | 9 | 2017 |
Time series distance measures: segmentation, classification, and clustering of temporal data S Spiegel Berlin, Technische Universität Berlin, Diss., 2015, 2015 | 9 | 2015 |