Direkt zum Inhalt
Markus Schneider

Prof. Dr. rer. nat. Markus Schneider

Leiter des Instituts für Künstliche Intelligenz
Schwerpunkt: Künstliche Intelligenz, Maschinelles Lernen, Intelligente Robotik
Fakultät Elektrotechnik und Informatik
Telefon
E-Mail markus.schneider@rwu.de
Raum E 112
Besuchsadresse
Gebäude E
Leibnizstr. 15
88250 Weingarten
Postadresse RWU Hochschule Ravensburg-Weingarten
University of Applied Sciences
Prof. Dr. rer. nat. Markus Schneider
Postfach 30 22
D 88216 Weingarten

Publikationen und Veröffentlichungen

Schneider, Markus

Expected Similarity Estimation for Large-Scale Anomaly Detection. Open Access Repositorium der Universität Ulm. PhD Dissertation (2017). doi:10.18725/OPARU-4222

Schneider, M.

Probability Inequalities for Kernel Embeddings in Sampling without Replacement. in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016) 66–74 (2016).

Schneider, M., Ertel, W. & Ramos, F.

Kernel Embeddings for Large-Scale Anomaly Detection. in International Conference on Machine Learning (ICML 2016): Anomaly Detection Workshop (2016).

Schneider, M., Ertel, W. & Ramos, F.

Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection. Machine Learning Journal 105, 305–333 (2016). doi:10.1007/s10994-016-5567-7

Schneider, M., Ertel, W. & Palm, G.

Constant Time EXPected Similarity Estimation for Large-Scale Anomaly Detection. in Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016) 12–20 (IOS Press, 2016). doi:10.3233/978-1-61499-672-9-12

Schneider, M., Ertel, W. & Palm, G.

Kernel Feature Maps from Arbitrary Distance Metrics. in KI 2015: Advances in Artificial Intelligence (eds. Hölldobler, S., Krötzsch, M., Peñaloza, R. & Rudolph, S.) 137–150 (Springer International Publishing, 2015). doi:10.1007/978-3-319-24489-1_11

Schneider, M., Ertel, W. & Palm, G.

Expected Similarity Estimation for Large-Scale Anomaly Detection. in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2015) 1–8 (IEEE, 2015). doi:10.1109/ijcnn.2015.7280331

Schneider, M. & Ramos, F.

Transductive Learning for Multi-Task Copula Processes. in European Conference on Artificial Intelligence (ECAI 2014) 1089–1090 (IOS Press, 2014). doi:10.3233/978-1-61499-419-0-1089

Schneider, M. & Ertel, W.

Robot Learning by Demonstration with local Gaussian process regression. in Intelligent Robots and Systems (IROS 2010), 255–260 (2010). doi:10.1109/IROS.2010.5650949