Skip to main content
Markus Schneider

Prof. Dr. rer. nat. Markus Schneider

Head of the Institute for Artificial Intelligence
Focus: Artificial intelligence, machine learning, intelligent robotics
Faculty of Electrical Engineering and Computer Science
Phone
Email markus.schneider@rwu.de
Room E 112
On campus
Building E
Leibnizstr. 15
88250 Weingarten
Postal address RWU Hochschule Ravensburg-Weingarten
University of Applied Sciences
Prof. Dr. rer. nat. Markus Schneider
P.O. Box 30 22
88216 Weingarten
Germany

Publications and publications

Schneider, Markus

Expected Similarity Estimation for Large-Scale Anomaly Detection. Open Access Repository of the University of 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