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 Holger Trittenbach |
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holger trittenbachZop9∂kit edu |
Lehrstuhl Karlsruher Institut für Technologie |
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Publikationen
HIPE – An energy-Status-Data set from industrial production.
Bischof, S.; Trittenbach, H.; Vollmer, M.; Werle, D.; Blank, T.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 599-603, ACM, New York (NY). doi:10.1145/3208903.3210278
Bischof, S.; Trittenbach, H.; Vollmer, M.; Werle, D.; Blank, T.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 599-603, ACM, New York (NY). doi:10.1145/3208903.3210278
On the tradeoff between energy data aggregation and clustering quality.
Trittenbach, H.; Bach, J.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 399-401, ACM, New York (NY). doi:10.1145/3208903.3212038
Trittenbach, H.; Bach, J.; Böhm, K.
2018. 9th ACM International Conference on Future Energy Systems, e-Energy 2018; Karlsruhe; Germany; 12 June 2018 through 15 June 2018, 399-401, ACM, New York (NY). doi:10.1145/3208903.3212038
Dimension-based subspace search for outlier detection [in press].
Trittenbach, H.; Böhm, K.
2018. International Journal of Data Science and Analytics. doi:10.1007/s41060-018-0137-7
Trittenbach, H.; Böhm, K.
2018. International Journal of Data Science and Analytics. doi:10.1007/s41060-018-0137-7
Towards Simulation-Data Science : A Case Study on Material Failures.
Trittenbach, H.; Gauch, M.; Böhm, K.; Schulz, K.
2018. Karlsruhe
Trittenbach, H.; Gauch, M.; Böhm, K.; Schulz, K.
2018. Karlsruhe
| Titel | Datum | Bearbeiter |
|---|---|---|
| User-centric Outlier Detection on Energy Data | July 2017 | Alexander Dick |
| Data-Driven Approaches to Predict Material Failure and to Analyze Material Models | Juni 2017 - Oktober 2017 | Martin Gauch |
| Impact of Aggregation Methods on High Volume Energy Data Streams | Mai 2017 - November 2017 | Jakob Bach |
| Improving the Interpretation of Outlier Scores in Subspaces | Dezember 2016 - März 2017 | Lukas Reister |
| Exploiting Neighborhood Relationships to Detect Suspicious Object | November 2016 - Mai 2017 | Ines Machinek |
| User Feedback for Outlier Detection in High Dimensional Data Spaces | November 2016 - Mai 2017 | Christian Olms |
| Generation of Synthetic Energy‐Consumption Data in Industrial Settings | September 2016 - März 2017 | Francesco Di Lillo |
| Angle-based Subspace Search for Outlier Detection in Word Vector Spaces | Juni 2016 - Oktober 2016 | Anika Bitsch |
| Titel | Datum | Bearbeiter |
|---|---|---|
| Interpretation of Outlier Detection Results | WS 16/17 | Marcel Groß |
| Active Learning for Unsupervised Anomaly Detection | WS 16/17 | Clemens Buchert |
| Titel | Typ | Semester |
|---|---|---|
| Praktikum: Analyse großer Datenbestände | Praktikum (P) | SS 2017 |
